Tootfinder

There's another layer to this as well, I think. Any social media feed interlaces horrible things with wonderful things in a completely contextually devoid list. A funny cat picture and a traumatic picture or video of violence are both "rated" in the same way, with the same imaginary internet points, without any differentiation between good and bad.
I feel like this is also cooking our brains a bit.

Beyond Detection -- Orchestrating Human-Robot-Robot Assistance via an Internet of Robotic Things Paradigm
Joseph Hunt, Koyo Fujii, Aly Magassouba, Praminda Caleb-Solly
https://arxiv.org/abs/2509.22296 …

Beyond Detection -- Orchestrating Human-Robot-Robot Assistance via an Internet of Robotic Things Paradigm
Hospital patient falls remain a critical and costly challenge worldwide. While conventional fall prevention systems typically rely on post-fall detection or reactive alerts, they also often suffer from high false positive rates and fail to address the underlying patient needs that lead to bed-exit attempts. This paper presents a novel system architecture that leverages the Internet of Robotic Things (IoRT) to orchestrate human-robot-robot interaction for proactive and personalized patient assis…

Securing the Internet of Medical Things (IoMT): Real-World Attack Taxonomy and Practical Security Measures
Suman Deb, Emil Lupu, Emm Mic Drakakis, Anil Anthony Bharath, Zhen Kit Leung, Guang Rui Ma, Anupam Chattopadhyay
https://arxiv.org/abs/2507.19609

Securing the Internet of Medical Things (IoMT): Real-World Attack Taxonomy and Practical Security Measures
The Internet of Medical Things (IoMT) has the potential to radically improve healthcare by enabling real-time monitoring, remote diagnostics, and AI-driven decision making. However, the connectivity, embedded intelligence, and inclusion of a wide variety of novel sensors expose medical devices to severe cybersecurity threats, compromising patient safety and data privacy. In addition, many devices also have direct capacity - individually or in conjunction with other IoMT devices - to perform act…

A Knowledge Distillation-empowered Adaptive Federated Reinforcement Learning Framework for Multi-Domain IoT Applications Scheduling
Zhiyu Wang, Mohammad Goudarzi, Mingming Gong, Rajkumar Buyya
https://arxiv.org/abs/2508.21328

A Knowledge Distillation-empowered Adaptive Federated Reinforcement Learning Framework for Multi-Domain IoT Applications Scheduling
The rapid proliferation of Internet of Things (IoT) applications across heterogeneous Cloud-Edge-IoT environments presents significant challenges in distributed scheduling optimization. Existing approaches face issues, including fixed neural network architectures that are incompatible with computational heterogeneity, non-Independent and Identically Distributed (non-IID) data distributions across IoT scheduling domains, and insufficient cross-domain collaboration mechanisms. This paper proposes…

AdapSCA-PSO: An Adaptive Localization Algorithm with AI-Based Hybrid SCA-PSO for IoT WSNs
Ze Zhang, Qian Dong, Wenhan Wang
https://arxiv.org/abs/2507.22317 https://

AdapSCA-PSO: An Adaptive Localization Algorithm with AI-Based Hybrid SCA-PSO for IoT WSNs
The accurate localization of sensor nodes is a fundamental requirement for the practical application of the Internet of Things (IoT). To enable robust localization across diverse environments, this paper proposes a hybrid meta-heuristic localization algorithm. Specifically, the algorithm integrates the Sine Cosine Algorithm (SCA), which is effective in global search, with Particle Swarm Optimization (PSO), which excels at local search. An adaptive switching module is introduced to dynamically s…

Our company sells products to test internet protocol implementations under unusual, but possible, situations. (Many fail.)
We sell worldwide, so we have to attach various code numbers to identify the type of product to the import/export (tariff/duty) government agents who make sure that things coming into their countries pay the proper fees.
Well, that list of code numbers appears to have been created in the 1970s and not updated since. So if you are selling a VHS VCR or a Fax m…

Foundations for Energy-Aware Zero-Energy Devices: From Energy Sensing to Adaptive Protocols
Onel L. A. L\'opez, Mateen Ashraf, Samer Nasser, Gabriel M. de Jesus, Ritesh Kumar Singh, Miltiadis C. Filippou, Jeroen Famaey
https://arxiv.org/abs/2507.22740

Foundations for Energy-Aware Zero-Energy Devices: From Energy Sensing to Adaptive Protocols
Zero-energy devices (ZEDs) are key enablers of sustainable Internet of Things networks by operating solely on harvested ambient energy. Their limited and dynamic energy budget calls for protocols that are energy-aware and intelligently adaptive. However, designing effective energy-aware protocols for ZEDs requires theoretical models that realistically reflect device constraints. Indeed, existing approaches often oversimplify key aspects such as energy information (EI) acquisition, task-level va…

Distributed Iterative ML and Message Passing for Grant-Free Cell-Free Massive MIMO Systems
Zilu Zhao, Christian Forsch, Laura Cottatellucci, Dirk Slock
https://arxiv.org/abs/2507.21363

Distributed Iterative ML and Message Passing for Grant-Free Cell-Free Massive MIMO Systems
Cell-Free (CF) Massive Multiple-Input Multiple-Output (MaMIMO) is considered one of the leading candidates for enabling next-generation wireless communication. With the growing interest in the Internet of Things (IoT), the Grant-Free (GF) access scheme has emerged as a promising solution to support massive device connectivity. The integration of GF and CF-MaMIMO introduces significant challenges, particularly in designing distributed algorithms for activity detection and pilot contamination mit…

Shilling Like It’s 1999: Ars, Anthropic, and the Internet of Other People’s Things https://musictechpolicy.com/2025/08/16/shilling-like-its-1999-ars-anthropic-and-the-internet-of-other-peoples-things/

Shilling Like It’s 1999: Ars, Anthropic, and the Internet of Other People’s Things
Ars Technica covers a massive AI copyright lawsuit with quotes from “public interest” groups tied to Google funding. This piece exposes the shill network, dismantles the ‘ownership is too har…

Google Workspace is full of dire warnings about how you can try things but they won't work for a long time (maybe). Sometimes that's because of DNS and Internet caching problems. Sometimes it's because Google made a decision in 2001 it was OK to store data in databases that didn't commit immediately and they thought it was OK to show the user inconsistent state. Twenty-four years later that awful decision persists, even if my data doesn't.

FAST-LoRa: An Efficient Simulation Framework for Evaluating LoRaWAN Networks and Transmission Parameter Strategies
Laura Acosta Garc\'ia, Juan Aznar Poveda, Fabian Margreiter, Antonio-Javier Garc\'ia S\'anchez, Joan Garc\'ia Haro, Thomas Fahringer, Jos\'e Lorente L\'opez, Jos\'e-V\'ictor Rodr\'iguez
https://

FAST-LoRa: An Efficient Simulation Framework for Evaluating LoRaWAN Networks and Transmission Parameter Strategies
The Internet of Things (IoT) has transformed many industries, and LoRaWAN (Long Range Wide Area Network), built on LoRa (Long Range) technology, has become a crucial solution for enabling scalable, low-cost, and energy-efficient communication in wide-area networks. Simulation tools are essential for optimizing the transmission parameters and, therefore, the energy efficiency and performance of LoRaWAN networks. While existing simulation frameworks accurately replicate real-world scenarios by in…

Spatially Correlated Blockage Aware Placement of RIS in IIoT Networks
Rashmi Kumari, Gourab Ghatak, Abhishek K. Gupta
https://arxiv.org/abs/2508.16946 https://

Spatially Correlated Blockage Aware Placement of RIS in IIoT Networks
We study the impact of deploying reconfigurable intelligent surfaces (RISs) in mitigating coverage gaps and enhancing transmission reliability in an industrial internet of things (IIoT) network. First, we consider a single blockage scenario and characterize the correlation between blocking events of the base station (BS)-user and the RIS-user links and study its impact on the probability of establishing a viable reflected link. Then, by considering multiple blockages, we derive the distribution…

An Efficient Recommendation Filtering-based Trust Model for Securing Internet of Things
Muhammad Ibn Ziauddin, Rownak Rahad Rabbi, SM Mehrab, Fardin Faiyaz, Mosarrat Jahan
https://arxiv.org/abs/2508.17304

An Efficient Recommendation Filtering-based Trust Model for Securing Internet of Things
Trust computation is crucial for ensuring the security of the Internet of Things (IoT). However, current trust-based mechanisms for IoT have limitations that impact data security. Sliding window-based trust schemes cannot ensure reliable trust computation due to their inability to select appropriate window lengths. Besides, recent trust scores are emphasized when considering the effect of time on trust. This can cause a sudden change in overall trust score based on recent behavior, potentially …

On IoT Communications Backhaul (2015) - How small Internet-of-Things (IoT) devices should talk to one another. #IoT #comms - https://www.

On IoT Communications Backhaul (2015)
How small Internet-of-Things (IoT) devices should talk to one another. #IoT #comms

Enhancing IoT Intrusion Detection Systems through Adversarial Training
Karma Gurung, Ashutosh Ghimire, Fathi Amsaad
https://arxiv.org/abs/2507.19739 https://

Enhancing IoT Intrusion Detection Systems through Adversarial Training
The augmentation of Internet of Things (IoT) devices transformed both automation and connectivity but revealed major security vulnerabilities in networks. We address these challenges by designing a robust intrusion detection system (IDS) to detect complex attacks by learning patterns from the NF-ToN-IoT v2 dataset. Intrusion detection has a realistic testbed through the dataset's rich and high-dimensional features. We combine distributed preprocessing to manage the dataset size with Fast Gradie…

Target Wake Time Scheduling for Time-sensitive and Energy-efficient Wi-Fi Networks
Fabio Busacca, Corrado Puligheddu, Francesco Raviglione, Riccardo Rusca, Claudio Casetti, Carla Fabiana Chiasserini, Sergio Palazzo
https://arxiv.org/abs/2509.26245

Target Wake Time Scheduling for Time-sensitive and Energy-efficient Wi-Fi Networks
Time Sensitive Networking (TSN) is fundamental for the reliable, low-latency networks that will enable the Industrial Internet of Things (IIoT). Wi-Fi has historically been considered unfit for TSN, as channel contention and collisions prevent deterministic transmission delays. However, this issue can be overcome by using Target Wake Time (TWT), which enables the access point to instruct Wi-Fi stations to wake up and transmit in non-overlapping TWT Service Periods (SPs), and sleep in the remain…

Protect your privacy – browsers and search engines
 
Surveillance has always been a core part of fascist regimes. This is still true today, but is even more dangerous due to new data aggregation and AI technologies. The Internet sites you visit and the things you search for become a part of the larger surveillance database of your activities. You can take action now to reduce the risk to yourself, your friends and your loved ones while you browse the Internet. You should start now …

Digital Twin Technologies in Predictive Maintenance: Enabling Transferability via Sim-to-Real and Real-to-Sim Transfer
Sizhe Ma, Katherine A. Flanigan, Mario Berg\'es
https://arxiv.org/abs/2507.18449

Digital Twin Technologies in Predictive Maintenance: Enabling Transferability via Sim-to-Real and Real-to-Sim Transfer
The advancement of the Internet of Things (IoT) and Artificial Intelligence has catalyzed the evolution of Digital Twins (DTs) from conceptual ideas to more implementable realities. Yet, transitioning from academia to industry is complex due to the absence of standardized frameworks. This paper builds upon the authors' previously established functional and informational requirements supporting standardized DT development, focusing on a crucial aspect: transferability. While existing DT research…

STL-GO: Spatio-Temporal Logic with Graph Operators for Distributed Systems with Multiple Network Topologies
Yiqi Zhao, Xinyi Yu, Bardh Hoxha, Georgios Fainekos, Jyotirmoy V. Deshmukh, Lars Lindemann
https://arxiv.org/abs/2507.15147

STL-GO: Spatio-Temporal Logic with Graph Operators for Distributed Systems with Multiple Network Topologies
Multi-agent systems (MASs) consisting of a number of autonomous agents that communicate, coordinate, and jointly sense the environment to achieve complex missions can be found in a variety of applications such as robotics, smart cities, and internet-of-things applications. Modeling and monitoring MAS requirements to guarantee overall mission objectives, safety, and reliability is an important problem. Such requirements implicitly require reasoning about diverse sensing and communication modalit…

Fast Revocable Attribute-Based Encryption with Data Integrity for Internet of Things
Yongjiao Li, Liang Zhu, Yalin Deng, Qikun Zhang, Zhenlei Wang, Zhu Cao
https://arxiv.org/abs/2509.20796

Fast Revocable Attribute-Based Encryption with Data Integrity for Internet of Things
Efficient and secure revocable attribute-based encryption (RABE) is vital for ensuring flexible and fine-grained access control and data sharing in cloud storage and outsourced data environments within the Internet of Things (IoT). However, current RABE schemes often struggle to achieve an optimal balance between efficiency, security, dynamic scalability, and other important features, which hampers their practical application. To overcome these limitations, we propose a fast RABE scheme with da…

🚨 I’ve just heard from @… after almost two days.
She’s alive but things are not good.
They left their tent because it was not safe but had to return because they had nowhere else to go. She couldn’t reach me because the Internet was down.
I’m trying to find out if there’s any amount of money we can send over that will mean that she and h…

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The unsettling rise of athlete stalkers, plus an NFL QB debate https://www.nytimes.com/athletic/6548086/2025/08/12/the-unsettling-rise-of-athlete-stalkers-plus-an-nfl-qb-debate/

Semantic-Aware Fuzzing: An Empirical Framework for LLM-Guided, Reasoning-Driven Input Mutation
Mengdi Lu, Steven Ding, Furkan Alaca, Philippe Charland
https://arxiv.org/abs/2509.19533

Semantic-Aware Fuzzing: An Empirical Framework for LLM-Guided, Reasoning-Driven Input Mutation
Security vulnerabilities in Internet-of-Things devices, mobile platforms, and autonomous systems remain critical. Traditional mutation-based fuzzers -- while effectively explore code paths -- primarily perform byte- or bit-level edits without semantic reasoning. Coverage-guided tools such as AFL++ use dictionaries, grammars, and splicing heuristics to impose shallow structural constraints, leaving deeper protocol logic, inter-field dependencies, and domain-specific semantics unaddressed. Conver…

Agent-based Simulation for Drone Charging in an Internet of Things Environment System
Leonardo Grando, Jos\'e Roberto Emiliano Leite, Edson Luiz Ursini
https://arxiv.org/abs/2509.10867

Agent-based Simulation for Drone Charging in an Internet of Things Environment System
This paper presents an agent-based simulation model for coordinating battery recharging in drone swarms, focusing on applications in Internet of Things (IoT) and Industry 4.0 environments. The proposed model includes a detailed description of the simulation methodology, system architecture, and implementation. One practical use case is explored: Smart Farming, highlighting how autonomous coordination strategies can optimize battery usage and mission efficiency in large-scale drone deployments. …

From Moose:

AirBreath Sensing: Protecting Over-the-Air Distributed Sensing Against Interference
Zhanwei Wang, Mingyao Cui, Huiling Yang, Qunsong Zeng, Min Sheng, Kaibin Huang
https://arxiv.org/abs/2508.11267

AirBreath Sensing: Protecting Over-the-Air Distributed Sensing Against Interference
A distinctive function of sixth-generation (6G) networks is the integration of distributed sensing and edge artificial intelligence (AI) to enable intelligent perception of the physical world. This resultant platform, termed integrated sensing and edge AI (ISEA), is envisioned to enable a broad spectrum of Internet-of-Things (IoT) applications, including remote surgery, autonomous driving, and holographic telepresence. Recently, the communication bottleneck confronting the implementation of an …

Man, I try hard to stay neutral-ish on the whole #genAI landscape, on the assumption that once the bubble pops, there’ll be gold nuggets in the rubble. But I read things like this and voices in the back of my head are shouting “burn it with fire!”

AI Generated 'Boring History' Videos Are Flooding YouTube and Drowning Out Real History
"These AI videos are just repeating things that are on the internet, so you end up with a very simplified version of the past."

CITADEL: Continual Anomaly Detection for Enhanced Learning in IoT Intrusion Detection
Elvin Li, Onat Gungor, Zhengli Shang, Tajana Rosing
https://arxiv.org/abs/2508.19450 https:…

CITADEL: Continual Anomaly Detection for Enhanced Learning in IoT Intrusion Detection
The Internet of Things (IoT), with its high degree of interconnectivity and limited computational resources, is particularly vulnerable to a wide range of cyber threats. Intrusion detection systems (IDS) have been extensively studied to enhance IoT security, and machine learning-based IDS (ML-IDS) show considerable promise for detecting malicious activity. However, their effectiveness is often constrained by poor adaptability to emerging threats and the issue of catastrophic forgetting during c…

An intrusion detection system in internet of things using grasshopper optimization algorithm and machine learning algorithms
Shiva Sattarpour, Ali Barati, Hamid Barati
https://arxiv.org/abs/2509.01724 …

An intrusion detection system in internet of things using grasshopper optimization algorithm and machine learning algorithms
The Internet of Things (IoT) has emerged as a foundational paradigm supporting a range of applications, including healthcare, education, agriculture, smart homes, and, more recently, enterprise systems. However, significant advancements in IoT networks have been impeded by security vulnerabilities and threats that, if left unaddressed, could hinder the deployment and operation of IoT based systems. Detecting unwanted activities within the IoT is crucial, as it directly impacts confidentiality, …

FedRP: A Communication-Efficient Approach for Differentially Private Federated Learning Using Random Projection
Mohammad Hasan Narimani, Mostafa Tavassolipour
https://arxiv.org/abs/2509.10041

FedRP: A Communication-Efficient Approach for Differentially Private Federated Learning Using Random Projection
Federated learning (FL) offers an innovative paradigm for collaborative model training across decentralized devices, such as smartphones, balancing enhanced predictive performance with the protection of user privacy in sensitive areas like Internet of Things (IoT) and medical data analysis. Despite its advantages, FL encounters significant challenges related to user privacy protection against potential attacks and the management of communication costs. This paper introduces a novel federated le…

A Scalable and Interoperable Platform for Transforming Building Information with Brick Ontology
Rozita Teymourzadeh, Yuya Nakazawa
https://arxiv.org/abs/2509.16259 https://

A Scalable and Interoperable Platform for Transforming Building Information with Brick Ontology
In the digital twin and building information era, many building automation companies searched for scalable methods to extract and analyze different building data, including Internet of Things (IoT) sensors, actuators, layout sections, zones, etc. The necessity for engineers to continuously manage the entire process for each new building creates scalability challenges. Furthermore, because construction information is sensitive, transferring data on vendor platforms via the cloud creates problems…

Timeliness-Aware Joint Source and Channel Coding for Adaptive Image Transmission
Xiaolei Yang, Zijing Wang, Zhijin Qin, Xiaoming Tao
https://arxiv.org/abs/2509.19754 https://

Timeliness-Aware Joint Source and Channel Coding for Adaptive Image Transmission
Accurate and timely image transmission is critical for emerging time-sensitive applications such as remote sensing in satellite-assisted Internet of Things. However, the bandwidth limitation poses a significant challenge in existing wireless systems, making it difficult to fulfill the requirements of both high-fidelity and low-latency image transmission. Semantic communication is expected to break through the performance bottleneck by focusing on the transmission of goal-oriented semantic infor…

Energy-Efficient Index and Code Index Modulations for Spread CPM Signals in Internet of Things
Long Yuan, Wenkun Wen, Junlin Liu, Peiran Wu, Minghua Xia
https://arxiv.org/abs/2508.10290

Energy-Efficient Index and Code Index Modulations for Spread CPM Signals in Internet of Things
The evolution of Internet of Things technologies is driven by four key demands: ultra-low power consumption, high spectral efficiency, reduced implementation cost, and support for massive connectivity. To address these challenges, this paper proposes two novel modulation schemes that integrate continuous phase modulation (CPM) with spread spectrum (SS) techniques. We begin by establishing the quasi-orthogonality properties of CPM-SS sequences. The first scheme, termed IM-CPM-SS, employs index m…

On IoT Communications Backhaul (2015) - How small Internet-of-Things (IoT) devices should talk to one another. #IoT #comms - https://www.

On IoT Communications Backhaul (2015)
How small Internet-of-Things (IoT) devices should talk to one another. #IoT #comms

Tomato Multi-Angle Multi-Pose Dataset for Fine-Grained Phenotyping
Yujie Zhang, Sabine Struckmeyer, Andreas Kolb, Sven Reichardt
https://arxiv.org/abs/2507.11279

Tomato Multi-Angle Multi-Pose Dataset for Fine-Grained Phenotyping
Observer bias and inconsistencies in traditional plant phenotyping methods limit the accuracy and reproducibility of fine-grained plant analysis. To overcome these challenges, we developed TomatoMAP, a comprehensive dataset for Solanum lycopersicum using an Internet of Things (IoT) based imaging system with standardized data acquisition protocols. Our dataset contains 64,464 RGB images that capture 12 different plant poses from four camera elevation angles. Each image includes manually annotate…

Accurate Trust Evaluation for Effective Operation of Social IoT Systems via Hypergraph-Enabled Self-Supervised Contrastive Learning
Botao Zhu, Xianbin Wang
https://arxiv.org/abs/2509.12240

Accurate Trust Evaluation for Effective Operation of Social IoT Systems via Hypergraph-Enabled Self-Supervised Contrastive Learning
Social Internet-of-Things (IoT) enhances collaboration between devices by endowing IoT systems with social attributes. However, calculating trust between devices based on complex and dynamic social attributes-similar to trust formation mechanisms in human society-poses a significant challenge. To address this issue, this paper presents a new hypergraph-enabled self-supervised contrastive learning (HSCL) method to accurately determine trust values between devices. To implement the proposed HSCL,…

A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networks
Jiaqi Wu, Jing Liu, Yang Liu, Lixu Wang, Zehua Wang, Wei Chen, Zijian Tian, Richard Yu, Victor C. M. Leung
https://arxiv.org/abs/2508.18803

A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networks
The proliferation of Internet of things (IoT) devices in smart cities, transportation, healthcare, and industrial applications, coupled with the explosive growth of AI-driven services, has increased demands for efficient distributed computing architectures and networks, driving cloud-edge-terminal collaborative intelligence (CETCI) as a fundamental paradigm within the artificial intelligence of things (AIoT) community. With advancements in deep learning, large language models (LLMs), and edge c…

NIST is done standardizing #ASCON, an encryption and hashing algorithm. I count that as a big win for #IoT security, in particular because the last review round's raised concerns were heeded and there is now a 32-bit tag mode usable for applications such as 802.15.4 link-layer security.
Congratulations…

NIST Finalizes ‘Lightweight Cryptography’ Standard to Protect Small Devices
Four related algorithms are now ready for use to protect data created and transmitted by the Internet of Things and other electronics

An Efficient Lightweight Blockchain for Decentralized IoT
Faezeh Dehghan Tarzjani, Mostafa Salehi
https://arxiv.org/abs/2508.19219 https://arxiv.org/pdf/25…

An Efficient Lightweight Blockchain for Decentralized IoT
The Internet of Things (IoT) is applied in various fields, and the number of physical devices connected to the IoT is increasingly growing. There are significant challenges to the IoT's growth and development, mainly due to the centralized nature and large-scale IoT networks. The emphasis on the decentralization of IoT's architecture can overcome challenges to IoT's capabilities. A promising decentralized platform for IoT is blockchain. Owing to IoT devices' limited resources, traditional conse…

Digital Twins in Industrial Applications: Concepts, Mathematical Modeling, and Use Cases
Ali Mohammad-Djafari
https://arxiv.org/abs/2507.12468 https://arxi…

MOHAF: A Multi-Objective Hierarchical Auction Framework for Scalable and Fair Resource Allocation in IoT Ecosystems
Kushagra Agrawal, Polat Goktas, Anjan Bandopadhyay, Debolina Ghosh, Junali Jasmine Jena, Mahendra Kumar Gourisaria
https://arxiv.org/abs/2508.14830

MOHAF: A Multi-Objective Hierarchical Auction Framework for Scalable and Fair Resource Allocation in IoT Ecosystems
The rapid growth of Internet of Things (IoT) ecosystems has intensified the challenge of efficiently allocating heterogeneous resources in highly dynamic, distributed environments. Conventional centralized mechanisms and single-objective auction models, focusing solely on metrics such as cost minimization or revenue maximization, struggle to deliver balanced system performance. This paper proposes the Multi-Objective Hierarchical Auction Framework (MOHAF), a distributed resource allocation mech…

A Computer Vision and Depth Sensor-Powered Smart Cane for Real-Time Obstacle Detection and Navigation Assistance for the Visually Impaired
Sunkalp Chandra, Umang Sharma, Devesh Khilnani
https://arxiv.org/abs/2508.16698

A Computer Vision and Depth Sensor-Powered Smart Cane for Real-Time Obstacle Detection and Navigation Assistance for the Visually Impaired
Visual impairment impacts more than 2.2 billion people worldwide, and it greatly restricts independent mobility and access. Conventional mobility aids - white canes and ultrasound-based intelligent canes - are inherently limited in the feedback they can offer and generally will not be able to differentiate among types of obstacles in dense or complex environments. Here, we introduce the IoT Cane, an internet of things assistive navigation tool that integrates real-time computer vision with a tr…

CattleSense - A Multisensory Approach to Optimize Cattle Well-Being
Srijesh Pillai, M. I. Jawid Nazir
https://arxiv.org/abs/2509.12617 https://arxiv.org/pd…

CattleSense - A Multisensory Approach to Optimize Cattle Well-Being
CattleSense is an innovative application of Internet of Things (IoT) technology for the comprehensive monitoring and management of cattle well-being. This research paper outlines the design and implementation of a sophisticated system using a Raspberry Pi Module 4B, RFID Card Reader, Electret Arduino Microphone Module, DHT11 Sensor, Arduino UNO, Neo-6M GPS Sensor, and Heartbeat Sensor. The system aims to provide real-time surveillance of the environment in which Cows are present and individual …

Age of Information Aided Intelligent Grant-Free Massive Access for Heterogeneous mMTC Traffic
Zhongwen Sun, Wei Chen, Yuxuan Sun, Bo Ai
https://arxiv.org/abs/2509.14503 https://…

Age of Information Aided Intelligent Grant-Free Massive Access for Heterogeneous mMTC Traffic
With the arrival of 6G, the Internet of Things (IoT) traffic is becoming more and more complex and diverse. To meet the diverse service requirements of IoT devices, massive machine-type communications (mMTC) becomes a typical scenario, and more recently, grant-free random access (GF-RA) presents a promising direction due to its low signaling overhead. However, existing GF-RA research primarily focuses on improving the accuracy of user detection and data recovery, without considering the heterog…

Enhancing Physical Layer Security in IoT-Based RF-FSO Integrated Networks: Multi-RIS Structures and their Impact on Secure Communication
Anika Tabassum Biva, Md. Ibrahim, A. S. M. Badrudduza, Imran Shafique Ansari
https://arxiv.org/abs/2509.15411

Enhancing Physical Layer Security in IoT-Based RF-FSO Integrated Networks: Multi-RIS Structures and their Impact on Secure Communication
Due to their ability to dynamically control the propagation environment, reconfigurable intelligent surfaces (RISs) offer a promising solution to address the challenges of $6$G wireless communication, especially in the context of Internet of Things (IoT) networks. This paper investigates a mixed communication model with multi-RIS-aided radio frequency (RF)-free space optics (FSO) to enhance the performance of IoT applications in complex environments. An eavesdropper is assumed to be present, at…

FlowXpert: Context-Aware Flow Embedding for Enhanced Traffic Detection in IoT Network
Chao Zha, Haolin Pan, Bing Bai, Jiangxing Wu, Ruyun Zhang
https://arxiv.org/abs/2509.20861 …

FlowXpert: Context-Aware Flow Embedding for Enhanced Traffic Detection in IoT Network
In the Internet of Things (IoT) environment, continuous interaction among a large number of devices generates complex and dynamic network traffic, which poses significant challenges to rule-based detection approaches. Machine learning (ML)-based traffic detection technology, capable of identifying anomalous patterns and potential threats within this traffic, serves as a critical component in ensuring network security. This study first identifies a significant issue with widely adopted feature e…

On IoT Communications Backhaul (2015) - How small Internet-of-Things (IoT) devices should talk to one another. #IoT #comms - https://www.

On IoT Communications Backhaul (2015)
How small Internet-of-Things (IoT) devices should talk to one another. #IoT #comms

An Internet of Intelligent Things Framework for Decentralized Heterogeneous Platforms
Vadim Allayev, Mahbubur Rahman
https://arxiv.org/abs/2509.10507 https://

An Internet of Intelligent Things Framework for Decentralized Heterogeneous Platforms
Internet of Intelligent Things (IoIT), an emerging field, combines the utility of Internet of Things (IoT) devices with the innovation of embedded AI algorithms. However, it does not come without challenges, and struggles regarding available computing resources, energy supply, and storage limitations. In particular, many impediments to IoIT are linked to the energy-efficient deployment of machine learning (ML)/deep learning (DL) models in embedded devices. Research has been conducted to design …

A Survey of TinyML Applications in Beekeeping for Hive Monitoring and Management
Willy Sucipto, Jianlong Zhou, Ray Seung Min Kwon, Fang Chen
https://arxiv.org/abs/2509.08822 htt…

A Survey of TinyML Applications in Beekeeping for Hive Monitoring and Management
Honey bee colonies are essential for global food security and ecosystem stability, yet they face escalating threats from pests, diseases, and environmental stressors. Traditional hive inspections are labor-intensive and disruptive, while cloud-based monitoring solutions remain impractical for remote or resource-limited apiaries. Recent advances in Internet of Things (IoT) and Tiny Machine Learning (TinyML) enable low-power, real-time monitoring directly on edge devices, offering scalable and no…

$AutoGuardX$: A Comprehensive Cybersecurity Framework for Connected Vehicles
Muhammad Ali Nadeem, Bishwo Prakash Pokharel, Naresh Kshetri, Achyut Shankar, Gokarna Sharma
https://arxiv.org/abs/2508.18155

$AutoGuardX$: A Comprehensive Cybersecurity Framework for Connected Vehicles
The rapid integration of Internet of Things (IoT) and interconnected systems in modern vehicles not only introduced a new era of convenience, automation, and connected vehicles but also elevated their exposure to sophisticated cyber threats. This is especially evident in US and Canada, where cyber-enabled auto theft has surged in recent years, revealing the limitations of existing security measures for connected vehicles. In response, this paper proposes $AutoGuardX$, a comprehensive cybersecur…

A Domain-specific Language and Architecture for Detecting Process Activities from Sensor Streams in IoT
Ronny Seiger, Daniel Locher, Marco Kaufmann, Aaron F. Kurz
https://arxiv.org/abs/2507.00686

A Domain-specific Language and Architecture for Detecting Process Activities from Sensor Streams in IoT
Modern Internet of Things (IoT) systems are equipped with a plethora of sensors providing real-time data about the current operations of their components, which is crucial for the systems' internal control systems and processes. However, these data are often too fine-grained to derive useful insights into the execution of the larger processes an IoT system might be part of. Process mining has developed advanced approaches for the analysis of business processes that may also be used in the conte…

Optimized Arithmetic Coding for Efficient Data Compression in the Resource-Constrained Internet of Things(IoT)
Vatsala Upadhyay, J. Kokila, Abhishek Vaish
https://arxiv.org/abs/2508.08840

Optimized Arithmetic Coding for Efficient Data Compression in the Resource-Constrained Internet of Things(IoT)
The Internet of Things (IoT) generates vast amounts of heterogeneous data, ranging from sensor readings to log alerts and images, that pose challenges to storage and data transmission in resource-constrained environments. In this context, lossless data compression techniques, like Arithmetic Coding, offer an effective solution owing to their high compression ratio. However, the standard Arithmetic Coding technique is computationally intensive, leading to high memory and processing overhead. Thi…

Talk with the Things: Integrating LLMs into IoT Networks
Alakesh Kalita
https://arxiv.org/abs/2507.17865 https://arxiv.org/pdf/2507.17865

Talk with the Things: Integrating LLMs into IoT Networks
The convergence of Large Language Models (LLMs) and Internet of Things (IoT) networks open new opportunities for building intelligent, responsive, and user-friendly systems. This work presents an edge-centric framework that integrates LLMs into IoT architectures to enable natural language-based control, context-aware decision-making, and enhanced automation. The proposed modular and lightweight Retrieval Augmented Generation (RAG)-based LLMs are deployed on edge computing devices connected to I…

Energy Management and Wake-up for IoT Networks Powered by Energy Harvesting
David Ernesto Ruiz-Guirola, Samuel Montejo-Sanchez, Israel Leyva-Mayorga, Zhu Han, Petar Popovski, Onel L. A. Lopez
https://arxiv.org/abs/2508.13825

Energy Management and Wake-up for IoT Networks Powered by Energy Harvesting
The rapid growth of the Internet of Things (IoT) presents sustainability challenges such as increased maintenance requirements and overall higher energy consumption. This motivates self-sustainable IoT ecosystems based on Energy Harvesting (EH). This paper treats IoT deployments in which IoT devices (IoTDs) rely solely on EH to sense and transmit information about events/alarms to a base station (BS). The objective is to effectively manage the duty cycling of the IoTDs to prolong battery life a…

COMponent-Aware Pruning for Accelerated Control Tasks in Latent Space Models
Ganesh Sundaram, Jonas Ulmen, Amjad Haider, Daniel G\"orges
https://arxiv.org/abs/2508.08144 ht…

COMponent-Aware Pruning for Accelerated Control Tasks in Latent Space Models
The rapid growth of resource-constrained mobile platforms, including mobile robots, wearable systems, and Internet-of-Things devices, has increased the demand for computationally efficient neural network controllers (NNCs) that can operate within strict hardware limitations. While deep neural networks (DNNs) demonstrate superior performance in control applications, their substantial computational complexity and memory requirements present significant barriers to practical deployment on edge dev…

A Model Aware AIGC Task Offloading Algorithm in IIoT Edge Computing
Xin Wang, Xiao Huan Li, Xun Wang
https://arxiv.org/abs/2507.11560 https://

A Model Aware AIGC Task Offloading Algorithm in IIoT Edge Computing
The integration of the Industrial Internet of Things (IIoT) with Artificial Intelligence-Generated Content (AIGC) offers new opportunities for smart manufacturing, but it also introduces challenges related to computation-intensive tasks and low-latency demands. Traditional generative models based on cloud computing are difficult to meet the real-time requirements of AIGC tasks in IIoT environments, and edge computing can effectively reduce latency through task offloading. However, the dynamic n…

Temperature-Resilient Reconfigurable PUF with Dual-Pulse Modulation based on SOT-MRAM Chip
Min Wang, Chuanpeng Jiang, Zhaohao Wang, Zhengyi Hou, Zhongkui Zhang, Yuanfu Zhao, Hongxi Liu, Weisheng Zhao
https://arxiv.org/abs/2508.16405

Temperature-Resilient Reconfigurable PUF with Dual-Pulse Modulation based on SOT-MRAM Chip
In the Internet of Things (IoT) era, hardware-based security solutions have become an emerging choice for enhancing end-terminal information security. As one of the hardware technologies, physical unclonable functions (PUFs) utilize the inherent variations in the manufacturing process to generate cryptographic keys. Reconfigurable PUFs (rPUFs), characterized by updating cryptographic keys, offer enhanced security ability for protecting massive amounts of data in dynamic operational scenarios. T…

QoS-Driven Satellite Constellation Design for LEO Satellite Internet of Things
Ming Ying, Xiaoming Chen, Qiao Qi, Zhaoyang Zhang
https://arxiv.org/abs/2509.00345 https://…

QoS-Driven Satellite Constellation Design for LEO Satellite Internet of Things
Low Earth orbit (LEO) satellite Internet of Things (IoT) has been identified as one of the important components of the sixth-generation (6G) non-terrestrial networks (NTN) to provide ubiquitous connectivity. Due to the low orbit altitude and high mobility, a massive number of satellites are required to form a global continuous coverage constellation, leading to a high construction cost. To this end, this paper proposes a LEO satellite IoT constellation design algorithm with the goal of minimizi…

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions
Ruichen Zhang, Guangyuan Liu, Yinqiu Liu, Changyuan Zhao, Jiacheng Wang, Yunting Xu, Dusit Niyato, Jiawen Kang, Yonghui Li, Shiwen Mao, Sumei Sun, Xuemin Shen, Dong In Kim
https://arxiv.org/abs/2508.18725

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions
The rapid expansion of sixth-generation (6G) wireless networks and the Internet of Things (IoT) has catalyzed the evolution from centralized cloud intelligence towards decentralized edge general intelligence. However, traditional edge intelligence methods, characterized by static models and limited cognitive autonomy, fail to address the dynamic, heterogeneous, and resource-constrained scenarios inherent to emerging edge networks. Agentic artificial intelligence (Agentic AI) emerges as a transf…

Performance Analysis of Pinching-Antenna-Enabled Internet of Things Systems
Han Zhang, Bingxin Zhang, Yizhe Zhao, Kun Yang, Guopeng Zhang
https://arxiv.org/abs/2509.04885 https:…

Performance Analysis of Pinching-Antenna-Enabled Internet of Things Systems
The pinching-antenna systems (PASS), which activate small dielectric particles along a dielectric waveguide, has recently emerged as a promising paradigm for flexible antenna deployment in next-generation wireless communication networks. While most existing studies assume rectangular indoor layouts with full coverage waveguide, practical deployments may involve geometric constraints, partial coverage, and non-negligible waveguide attenuation. This paper presents the first analytical investigati…

Joint AP Selection and Power Allocation for Unicast-Multicast Cell-Free Massive MIMO
Mustafa S. Abbas, Zahra Mobini, Hien Quoc Ngo, Hyundong Shin, Michail Matthaiou
https://arxiv.org/abs/2508.13771

Joint AP Selection and Power Allocation for Unicast-Multicast Cell-Free Massive MIMO
Joint unicast and multicast transmissions are becoming increasingly important in practical wireless systems, such as Internet of Things networks. This paper investigates a cell-free massive multiple-input multiple-output system that simultaneously supports both transmission types, with multicast serving multiple groups. Exact closed-form expressions for the achievable downlink spectral efficiency (SE) of both unicast and multicast users are derived for zero-forcing and maximum ratio precoding d…

Lightweight Intrusion Detection System Using a Hybrid CNN and ConvNeXt-Tiny Model for Internet of Things Networks
Fatemeh Roshanzadeh, Hamid Barati, Ali Barati
https://arxiv.org/abs/2509.06202

Lightweight Intrusion Detection System Using a Hybrid CNN and ConvNeXt-Tiny Model for Internet of Things Networks
The rapid expansion of Internet of Things (IoT) systems across various domains such as industry, smart cities, healthcare, manufacturing, and government services has led to a significant increase in security risks, threatening data integrity, confidentiality, and availability. Consequently, ensuring the security and resilience of IoT systems has become a critical requirement. In this paper, we propose a lightweight and efficient intrusion detection system (IDS) for IoT environments, leveraging …

Large Language Model-Empowered Decision Transformer for UAV-Enabled Data Collection
Zhixion Chen, Jiangzhou Wang, and Hyundong Shin, Arumugam Nallanathan
https://arxiv.org/abs/2509.13934

Large Language Model-Empowered Decision Transformer for UAV-Enabled Data Collection
The deployment of unmanned aerial vehicles (UAVs) for reliable and energy-efficient data collection from spatially distributed devices holds great promise in supporting diverse Internet of Things (IoT) applications. Nevertheless, the limited endurance and communication range of UAVs necessitate intelligent trajectory planning. While reinforcement learning (RL) has been extensively explored for UAV trajectory optimization, its interactive nature entails high costs and risks in real-world environ…

Optimizing Task Scheduling in Fog Computing with Deadline Awareness
Mohammad Sadegh Sirjani, Somayeh Sobati-Moghadam
https://arxiv.org/abs/2509.07378 https://

Optimizing Task Scheduling in Fog Computing with Deadline Awareness
The rise of Internet of Things (IoT) devices has led to the development of numerous applications that require quick responses and low latency. Fog computing has emerged as a solution for processing these IoT applications, but it faces challenges such as resource allocation and job scheduling. Therefore, it is crucial to determine how to assign and schedule tasks on Fog nodes. A well-designed job scheduling algorithm can help decrease energy usage and improve response times for application reque…

Low-Power and Accurate IoT Monitoring Under Radio Resource Constraint
Takaho Shimokasa, Hiroyuki Yomo, Federico Chiariotti, Junya Shiraishi, Petar Popovski
https://arxiv.org/abs/2507.15338

Low-Power and Accurate IoT Monitoring Under Radio Resource Constraint
This paper investigates how to achieve both low-power operations of sensor nodes and accurate state estimation using Kalman filter for internet of things (IoT) monitoring employing wireless sensor networks under radio resource constraint. We consider two policies used by the base station to collect observations from the sensor nodes: (i) an oblivious policy, based on statistics of the observations, and (ii) a decentralized policy, based on autonomous decision of each sensor based on its instant…

A Grant-free Coded Random Access Scheme for Near-field Communications
Enrico Testi, Giulia Torcolacci, Nicol\`o Decarli, Davide Dardari, Enrico Paolini
https://arxiv.org/abs/2508.15673

A Grant-free Coded Random Access Scheme for Near-field Communications
The industrial Internet of things (IIoT) is revolutionizing industrial processes by facilitating massive machine-type communications among countless interconnected devices. To efficiently handle the resulting large-scale and sporadic traffic, grant-free random access protocols-especially coded random access (CRA)-have emerged as scalable and reliable solutions. At the same time, advancements in wireless hardware, including extremely large-scale MIMO arrays and high-frequency communication (e.g.…

A Robust Cross-Domain IDS using BiGRU-LSTM-Attention for Medical and Industrial IoT Security
Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari, Mohamed Chahine Ghanem
https://arxiv.org/abs/2508.12470 …

A Robust Cross-Domain IDS using BiGRU-LSTM-Attention for Medical and Industrial IoT Security
The increased Internet of Medical Things IoMT and the Industrial Internet of Things IIoT interconnectivity has introduced complex cybersecurity challenges, exposing sensitive data, patient safety, and industrial operations to advanced cyber threats. To mitigate these risks, this paper introduces a novel transformer-based intrusion detection system IDS, termed BiGAT-ID a hybrid model that combines bidirectional gated recurrent units BiGRU, long short-term memory LSTM networks, and multi-head att…

Secrecy Offloading Analysis of UAV-assisted NOMA-MEC Incorporating WPT in IoT Networks
Gia-Huy Nguyen, Anh-Nhat Nguyen, Minh-Sang Nguyen, Khai Nguyen, Tung-Son Ngo, Ngoc-Anh Bui, Phuong-Chi Le, Manh-Duc Hoang
https://arxiv.org/abs/2507.08352

Secrecy Offloading Analysis of UAV-assisted NOMA-MEC Incorporating WPT in IoT Networks
This article studies the efficiency of secrecy data offloading for an unmanned aerial vehicle (UAV)-assisted nonorthogonal multiple access (NOMA)-integrated mobile-edge computing (MEC) incorporating wireless power transfer (WPT) within an Internet of Things (IoT) network. Specifically, this study assumes an UAV to function in dual roles: as a mobile computation platform and as an aerial power-supply station, offering substantial advantages for resource-constrained edge devices (EDs) in mitigati…

How To Mitigate And Defend Against DDoS Attacks In IoT Devices
Ifiyemi Leigha, Basak Comlekcioglu, Maria Pilar Bezanilla
https://arxiv.org/abs/2507.11772 h…

How To Mitigate And Defend Against DDoS Attacks In IoT Devices
Distributed Denial of Service (DDoS) attacks have become increasingly prevalent and dangerous in the context of Internet of Things (IoT) networks, primarily due to the low-security configurations of many connected devices. This paper analyzes the nature and impact of DDoS attacks such as those launched by the Mirai botnet, and proposes layered mitigation strategies tailored to IoT environments. Key solutions explored include IPv6 Unique Local Addresses (ULA), edge computing, software-defined ne…

Age of Information Optimization in Laser-charged UAV-assisted IoT Networks: A Multi-agent Deep Reinforcement Learning Method
Geng Sun, Likun Zhang, Jiahui Li, Jing Wu, Jiacheng Wang, Zemin Sun, Changyuan Zhao, Victor C. M. Leung
https://arxiv.org/abs/2507.08429

Age of Information Optimization in Laser-charged UAV-assisted IoT Networks: A Multi-agent Deep Reinforcement Learning Method
The integration of unmanned aerial vehicles (UAVs) with Internet of Things (IoT) networks offers promising solutions for efficient data collection. However, the limited energy capacity of UAVs remains a significant challenge. In this case, laser beam directors (LBDs) have emerged as an effective technology for wireless charging of UAVs during operation, thereby enabling sustained data collection without frequent returns to charging stations (CSs). In this work, we investigate the age of informa…

Integrated user scheduling and beam steering in over-the-air federated learning for mobile IoT
Shengheng Liu, Ningning Fu, Zhonghao Zhang, Yongming Huang, Tony Q. S. Quek
https://arxiv.org/abs/2508.00341

Integrated user scheduling and beam steering in over-the-air federated learning for mobile IoT
The rising popularity of Internet of things (IoT) has spurred technological advancements in mobile internet and interconnected systems. While offering flexible connectivity and intelligent applications across various domains, IoT service providers must gather vast amounts of sensitive data from users, which nonetheless concomitantly raises concerns about privacy breaches. Federated learning (FL) has emerged as a promising decentralized training paradigm to tackle this challenge. This work focus…

Joint Optimization of Computation Offloading and Resource Allocation in ISAC-assisted SAGIN-based IoT
Sooyeob Jung, Seongah Jeong, Jinkyu Kang
https://arxiv.org/abs/2509.08238 h…

Joint Optimization of Computation Offloading and Resource Allocation in ISAC-assisted SAGIN-based IoT
In this letters, an energy-efficient integrated sensing and communication (ISAC) for space-air-ground integrated network (SAGIN)-based Internet of Things (IoT) systems is proposed to facilitate wide coverage and real-time 6G services. For processing a sizable data collected at a IoT device, a hybrid edge computing scheme is applied with the cloudlets mounted at autonomous aerial vehicle (AAV) and low earth orbit (LEO) satellite, where the AAV with multiple antennas performs uplink sensing of th…

Data-driven Trust Bootstrapping for Mobile Edge Computing-based Industrial IoT Services
Prabath Abeysekara, Hai Dong
https://arxiv.org/abs/2508.12560 https://

Data-driven Trust Bootstrapping for Mobile Edge Computing-based Industrial IoT Services
We propose a data-driven and context-aware approach to bootstrap trustworthiness of homogeneous Internet of Things (IoT) services in Mobile Edge Computing (MEC) based industrial IoT (IIoT) systems. The proposed approach addresses key limitations in adapting existing trust bootstrapping approaches into MEC-based IIoT systems. These key limitations include, the lack of opportunity for a service consumer to interact with a lesser-known service over a prolonged period of time to get a robust measur…

RIS-assisted ISAC Systems for Industrial Revolution 6.0: Exploring the Near-field and Far-field Coexistence
Seonghoon Yoo, Jaemin Jung, Seongah Jeong, Jinkyu Kang, Markku Juntti, Joonhyuk Kang
https://arxiv.org/abs/2507.07643

RIS-assisted ISAC Systems for Industrial Revolution 6.0: Exploring the Near-field and Far-field Coexistence
The Industrial Internet of Things (IIoT) has emerged as a key technology for realizing the vision of Industry 6.0, requiring the seamless integration of diverse connected devices. In particular, integrated sensing and communication (ISAC) plays a critical role in supporting real-time control and automation within IIoT systems. In this paper, we explore reconfigurable intelligent surface (RIS)-assisted ISAC systems for IIoT in the coexistence of near-field and far-field regions. The system consi…

RIS-assisted Data Collection and Wireless Power Transfer in Low-altitude Wireless Networks
Wenwen Xie, Geng Sun, Jiahui Li, Jiacheng Wang, Yinqiu Liu, Dusit Niyato, Dong In Kim, Shiwen Mao
https://arxiv.org/abs/2509.19651

RIS-assisted Data Collection and Wireless Power Transfer in Low-altitude Wireless Networks
Low-altitude wireless networks (LAWNs) have become effective solutions for collecting data from low-power Internet-of-Things devices (IoTDs) in remote areas with limited communication infrastructure. However, some outdoor IoTDs deployed in such areas face both energy constraints and low-channel quality challenges, making it challenging to ensure timely data collection from these IoTDs in LAWNs. In this work, we investigate a reconfigurable intelligent surface (RIS)-assisted uncrewed aerial vehi…

Threats and Security Strategies for IoMT Infusion Pumps
Ramazan Yener, Muhammad Hassan, Masooda Bashir
https://arxiv.org/abs/2509.14604 https://arxiv.org/p…

Threats and Security Strategies for IoMT Infusion Pumps
The integration of the Internet of Medical Things (IoMT) into healthcare systems has transformed patient care by enabling real-time monitoring, enhanced diagnostics, and enhanced operational efficiency. However, this increased connectivity has also expanded the attack surface for cybercriminals, raising significant cybersecurity and privacy concerns. This study focuses on the cybersecurity vulnerabilities of IoMT infusion pumps, which are critical devices in modern healthcare. Through a targete…

Efficient Byzantine Consensus MechanismBased on Reputation in IoT Blockchain
Xu Yuan, Fang Luo, Muhammad Zeeshan Haider, Zhikui Chen, Yucheng Li
https://arxiv.org/abs/2508.01856

Efficient Byzantine Consensus MechanismBased on Reputation in IoT Blockchain
Blockchain technology has advanced rapidly in recent years and is now widely used in a variety of fields. Blockchain appears to be one of the best solutions for managing massive heterogeneous devices while achieving advanced data security and data reputation, particularly in the field of large-scale IoT (Internet of Things) networks. Despite the numerous advantages, there are still challenges while deploying IoT applications on blockchain systems due to the limited storage, power, and computing…

IRS-Assisted IoT Activity Detection Under Asynchronous Transmission and Heterogeneous Powers: Detectors and Performance Analysis
Amirhossein Taherpour, Somayeh Khani, Abbas Taherpour, Tamer Khattab
https://arxiv.org/abs/2508.05959

IRS-Assisted IoT Activity Detection Under Asynchronous Transmission and Heterogeneous Powers: Detectors and Performance Analysis
This paper addresses the problem of activity detection in distributed Internet of Things (IoT) networks, where devices employ asynchronous transmissions with heterogeneous power levels to report their local observations. The system leverages an intelligent reflecting surface (IRS) to enhance detection reliability, with optional incorporation of a direct line-of-sight (LoS) path. We formulate the detection problem as a binary hypothesis test and develop four detectors: an optimal detector alongs…

QTCAJOSA: Low-Complexity Joint Offloading and Subchannel Allocation for NTN-Enabled IoMT
Alejandro Flores C., Konstantinos Ntontin, Ashok Bandi, Symeon Chatzinotas
https://arxiv.org/abs/2507.13242

QTCAJOSA: Low-Complexity Joint Offloading and Subchannel Allocation for NTN-Enabled IoMT
In this work, we consider the resource allocation problem for task offloading from Internet of Medical Things (IoMT) devices, to a non-terrestrial network. The architecture considers clusters of IoMT devices that offload their tasks to a dedicated unmanned aerial vehicle (UAV) serving as a multi-access edge computing (MEC) server, which can compute the task or further offload it to an available high-altitude platform station (HAPS) or to a low-earth orbit (LEO) satellite for remote computing. W…

Qualitative Assessment of Low Power Wide Area Network Protocols and their Security Aspect
Wesley dos Reis Bezerra, Lais Machado Bezerra, Carlos Becker Westphal
https://arxiv.org/abs/2507.08677

Qualitative Assessment of Low Power Wide Area Network Protocols and their Security Aspect
There are currently many communication options in the Internet of Things, even in particular areas such as constrained and battery-powered devices, such as Low Power Wide Area Networks. Understanding the differences and characteristics of each option is a challenge, even for professionals and researchers in the field. To meet this need, this work analyses the qualitative characteristics of Low Power Wide Area Network protocols and the challenges and opportunities of using constrained devices fo…

Reporte de vulnerabilidades en IIoT. Proyecto DEFENDER
Pedro Almansa Jim\'enez, Lorenzo Fern\'andez Maim\'o, \'Angel Luis Per\'ales G\'omez
https://arxiv.org/abs/2507.10819

Reporte de vulnerabilidades en IIoT. Proyecto DEFENDER
The main objective of this technical report is to conduct a comprehensive study on devices operating within Industrial Internet of Things (IIoT) environments, describing the scenarios that define this category and analysing the vulnerabilities that compromise their security. To this end, the report seeks to identify and examine the main classes of IIoT devices, detailing their characteristics, functionalities, and roles within industrial systems. This analysis enables a better understanding of …

Reputation-based partition scheme for IoT security
Zhikui Chen, Muhammad Zeeshan Haider, Naiwen Luo, Shuo Yu, Xu Yuan, Yaochen Zhang, Tayyaba Noreen
https://arxiv.org/abs/2508.03981

Reputation-based partition scheme for IoT security
With the popularity of smart terminals, such as the Internet of Things, crowdsensing is an emerging data aggregation paradigm, which plays a pivotal role in data-driven applications. There are some key issues in the development of crowdsensing such as platform security and privacy protection. As the crowdsensing is usually managed by a centralized platform, centralized management will bring various security vulnerabilities and scalability issues. To solve these issues, an effective reputation-b…

On Performance of IoT Networks with Coordinated NOMA Transmission: Covert Monitoring and Information Decoding
Thai-Hoc Vu, Anh-Tu Le, Ngo Hoang Tu, Tan N. Nguyen, Miroslav Voznak
https://arxiv.org/abs/2509.01935

On Performance of IoT Networks with Coordinated NOMA Transmission: Covert Monitoring and Information Decoding
This work investigates the covertness and security performance of Internet-of-Things (IoTs) networks under Rayleigh fading environments. Specifically, a cellular source transmits covert information to cell-edge users with the assistance of an IoT master node, employing a coordinated direct and relay transmission strategy combined with non-orthogonal multiple access (NOMA). This approach not only enhances spectrum utilization but also generates friendly interference to complicate a warden's surv…

Enabling Cyber Security Education through Digital Twins and Generative AI
Vita Santa Barletta, Vito Bavaro, Miriana Calvano, Antonio Curci, Antonio Piccinno, Davide Pio Posa
https://arxiv.org/abs/2507.17518

Enabling Cyber Security Education through Digital Twins and Generative AI
Digital Twins (DTs) are gaining prominence in cybersecurity for their ability to replicate complex IT (Information Technology), OT (Operational Technology), and IoT (Internet of Things) infrastructures, allowing for real time monitoring, threat analysis, and system simulation. This study investigates how integrating DTs with penetration testing tools and Large Language Models (LLMs) can enhance cybersecurity education and operational readiness. By simulating realistic cyber environments, this a…

Backscattering-Based Security in Wireless Power Transfer Applied to Battery-Free BLE Sensors
Taki Eddine Djidjekh (INSA Toulouse, LAAS-MINC), Ga\"el Loubet (LAAS-MINC, INSA Toulouse), Alexandru Takacs (LAAS-MINC, UT)
https://arxiv.org/abs/2507.13042

Backscattering-Based Security in Wireless Power Transfer Applied to Battery-Free BLE Sensors
The integration of security and energy efficiency in Internet of Things systems remains a critical challenge, particularly for battery-free and resource-constrained devices. This paper explores the scalability and protocol-agnostic nature of a backscattering-based security mechanism by integrating it into Bluetooth Low Energy battery-free Wireless Sensor Network. The proposed approach leverages the Wireless Power Transfer link, traditionally used for energy harvesting, to generate additional id…

User Head Movement-Predictive XR in Immersive H2M Collaborations over Future Enterprise Networks
Sourav Mondal, Elaine Wong
https://arxiv.org/abs/2507.15254

User Head Movement-Predictive XR in Immersive H2M Collaborations over Future Enterprise Networks
The evolution towards future generation of mobile systems and fixed wireless networks is primarily driven by the urgency to support high-bandwidth and low-latency services across various vertical sectors. This endeavor is fueled by smartphones as well as technologies like industrial internet of things, extended reality (XR), and human-to-machine (H2M) collaborations for fostering industrial and social revolutions like Industry 4.0/5.0 and Society 5.0. To ensure an ideal immersive experience and…

Leveraging Blockchain and Proxy Re-Encryption to secure Medical IoT Records
Abdou-Essamad Jabri (UPJV, MIS), C. Drocourt (UPJV, MIS), Mostafa Azizi (UPJV, MIS), Gil Utard (UPJV, MIS)
https://arxiv.org/abs/2509.08402

Leveraging Blockchain and Proxy Re-Encryption to secure Medical IoT Records
The integration of the Internet of Things (IoT) in healthcare has revolutionized patient monitoring and data collection, allowing real-time tracking of vital signs, remote diagnostics, and automated medical responses. However, the transmission and storage of sensitive medical data introduce significant security and privacy challenges. To address these concerns, blockchain technology provides a decentralized and immutable ledger that ensures data integrity, , and transparency. Unlike public bloc…

Duty-Cycling is Not Enough in Constrained IoT Networking: Revealing the Energy Savings of Dynamic Clock Scaling
Michel Rottleuthner, Thomas C. Schmidt, Matthias W\"ahlisch
https://arxiv.org/abs/2508.09620

Duty-Cycling is Not Enough in Constrained IoT Networking: Revealing the Energy Savings of Dynamic Clock Scaling
Minimizing energy consumption of low-power wireless nodes is a persistent challenge from the constrained Internet of Things (IoT). In this paper, we start from the observation that constrained IoT devices have largely different hardware (im-)balances than full-scale machines. We find that the performance gap between MCU and network throughput on constrained devices enables minimal energy delay product (EDP) for IoT networking at largely reduced clock frequencies. We analyze the potentials by in…

Design and Development of a Scalable and Energy-Efficient Localization Framework Leveraging LoRa Ranging-Capable Transceivers
Hasan Albinsaid, Bodhibrata Mukhopadhyay, Mohamed-Slim Alouini
https://arxiv.org/abs/2509.08488

Design and Development of a Scalable and Energy-Efficient Localization Framework Leveraging LoRa Ranging-Capable Transceivers
Precise and energy-efficient localization is a critical requirement in many Internet of Things (IoT) applications, particularly in large-scale deployments such as asset tagging, agriculture, and smart cities, where long battery life and cost-effectiveness are crucial. The Semtech SX1280 LoRa transceiver presents a promising solution for IoT localization. It combines low cost, low power, and precise ranging capability over distances of up to 1 km. However, the ranging process requires two device…

Load-Altering Attacks Against Power Grids: A Case Study Using the GB-36 Bus System Open Dataset
Syed Irtiza Maksud, Subhash Lakshminarayana
https://arxiv.org/abs/2508.08945 http…

Load-Altering Attacks Against Power Grids: A Case Study Using the GB-36 Bus System Open Dataset
The growing digitalization and the rapid adoption of high-powered Internet-of-Things (IoT)-enabled devices (e.g., EV charging stations) have increased the vulnerability of power grids to cyber threats. In particular, the so-called Load Altering Attacks (LAAs) can trigger rapid frequency fluctuations and potentially destabilize the power grid. This paper aims to bridge the gap between academic research and practical application by using open-source datasets released by grid operators. It investi…

Spectral Feature Extraction for Robust Network Intrusion Detection Using MFCCs
HyeYoung Lee, Muhammad Nadeem, Pavel Tsoi
https://arxiv.org/abs/2507.10622 h…

Spectral Feature Extraction for Robust Network Intrusion Detection Using MFCCs
The rapid expansion of Internet of Things (IoT) networks has led to a surge in security vulnerabilities, emphasizing the critical need for robust anomaly detection and classification techniques. In this work, we propose a novel approach for identifying anomalies in IoT network traffic by leveraging the Mel-frequency cepstral coefficients (MFCC) and ResNet-18, a deep learning model known for its effectiveness in feature extraction and image-based tasks. Learnable MFCCs enable adaptive spectral f…

SAGE: Sample-Aware Guarding Engine for Robust Intrusion Detection Against Adversarial Attacks
Jing Chen, Onat Gungor, Zhengli Shang, Tajana Rosing
https://arxiv.org/abs/2509.08091

SAGE: Sample-Aware Guarding Engine for Robust Intrusion Detection Against Adversarial Attacks
The rapid proliferation of the Internet of Things (IoT) continues to expose critical security vulnerabilities, necessitating the development of efficient and robust intrusion detection systems (IDS). Machine learning-based intrusion detection systems (ML-IDS) have significantly improved threat detection capabilities; however, they remain highly susceptible to adversarial attacks. While numerous defense mechanisms have been proposed to enhance ML-IDS resilience, a systematic approach for selecti…

Performance Evaluation of LoRa for IoT Applications in Non-Terrestrial Networks via ns-3
Alessandro Traspadini, Michele Zorzi, Marco Giordani
https://arxiv.org/abs/2509.02811 ht…

Performance Evaluation of LoRa for IoT Applications in Non-Terrestrial Networks via ns-3
The integration of Internet of Things (IoT) and Non-Terrestrial Networks (NTNs) has emerged as a key paradigm to provide connectivity for sensors and actuators via satellite gateways in remote areas where terrestrial infrastructure is limited or unavailable. Among other Low-Power Wide-Area Network (LPWAN) technologies for IoT, Long Range (LoRa) holds great potential given its long range, energy efficiency, and flexibility. In this paper, we explore the feasibility and performance of LoRa to sup…

CRAFT: Latency and Cost-Aware Genetic-Based Framework for Node Placement in Edge-Fog Environments
Soheil Mahdizadeh, Amir Mahdi Rasouli, Mohammad Pourashory, Sadra Galavani, Mohsen Ansari
https://arxiv.org/abs/2507.12445

CRAFT: Latency and Cost-Aware Genetic-Based Framework for Node Placement in Edge-Fog Environments
Reducing latency in the Internet of Things (IoT) is a critical concern. While cloud computing facilitates communication, it falls short of meeting real-time requirements reliably. Edge and fog computing have emerged as viable solutions by positioning computing nodes closer to end users, offering lower latency and increased processing power. An edge-fog framework comprises various components, including edge and fog nodes, whose strategic placement is crucial as it directly impacts latency and sy…

Extreme Learning Machine Based System for DDoS Attacks Detections on IoMT Devices
Nelly Elsayed, Lily Dzamesi, Zag ElSayed, Murat Ozer
https://arxiv.org/abs/2507.05132

Extreme Learning Machine Based System for DDoS Attacks Detections on IoMT Devices
The Internet of Medical Things (IoMT) represents a paradigm shift in the healthcare sector, enabling the interconnection of medical devices, sensors, and systems to enhance patient monitoring, diagnosis, and management. The rapid evolution of IoMT presents significant benefits to the healthcare domains. However, there is a rapid increase in distributed denial of service (DDoS) attacks on the IoMT networks due to several vulnerabilities in the IoMT-connected devices, which negatively impact pati…

Optimizing Age of Trust and Throughput in Multi-Hop UAV-Aided IoT Networks
Yizhou Luo, Kwan-Wu Chin, Ruyi Guan, Xi Xiao, Caimeng Wang, Jingyin Feng, Tengjiao He
https://arxiv.org/abs/2507.03950

Optimizing Age of Trust and Throughput in Multi-Hop UAV-Aided IoT Networks
Devices operating in Internet of Things (IoT) networks may be deployed across vast geographical areas and interconnected via multi-hop communications. Further, they may be unguarded. This makes them vulnerable to attacks and motivates operators to check on devices frequently. To this end, we propose and study an Unmanned Aerial Vehicle (UAV)-aided attestation framework for use in IoT networks with a charging station powered by solar. A key challenge is optimizing the trajectory of the UAV to en…

Arbiter PUF: Uniqueness and Reliability Analysis Using Hybrid CMOS-Stanford Memristor Model
Tanvir Rahman, A. B. M. Harun-ur Rashid
https://arxiv.org/abs/2507.04461

Arbiter PUF: Uniqueness and Reliability Analysis Using Hybrid CMOS-Stanford Memristor Model
In an increasingly interconnected world, protecting electronic devices has grown more crucial because of the dangers of data extraction, reverse engineering, and hardware tampering. Producing chips in a third-party manufacturing company can let hackers change the design. As the Internet of Things (IoT) proliferates, physical attacks happen more, and conventional cryptography techniques do not function well. In this paper, we investigate the design and assessment of PUFs using the Stanford Memri…

System Security Framework for 5G Advanced /6G IoT Integrated Terrestrial Network-Non-Terrestrial Network (TN-NTN) with AI-Enabled Cloud Security
Sasa Maric, Rasil Baidar, Robert Abbas, Sam Reisenfeld
https://arxiv.org/abs/2508.05707

System Security Framework for 5G Advanced /6G IoT Integrated Terrestrial Network-Non-Terrestrial Network (TN-NTN) with AI-Enabled Cloud Security
The integration of Terrestrial Networks (TN) and Non-Terrestrial Networks (NTN), including 5G Advanced/6G and the Internet of Things (IoT) technologies, using Low Earth Orbit (LEO) satellites, high-altitude platforms (HAPS), and Unmanned Aerial Vehicles (UAVs), is redefining the landscape of global connectivity. This paper introduces a new system-level security framework for 5G Advanced/6G IoT-integrated TN-NTN architectures with AI-native-enabled cloud security. Due to the heterogeneity, scale…

IoTFuzzSentry: A Protocol Guided Mutation Based Fuzzer for Automatic Vulnerability Testing in Commercial IoT Devices
Priyanka Rushikesh Chaudhary, Rajib Ranjan Maiti
https://arxiv.org/abs/2509.09158

IoTFuzzSentry: A Protocol Guided Mutation Based Fuzzer for Automatic Vulnerability Testing in Commercial IoT Devices
Protocol fuzzing is a scalable and cost-effective technique for identifying security vulnerabilities in deployed Internet of Things devices. During their operational phase, IoT devices often run lightweight servers to handle user interactions, such as video streaming or image capture in smart cameras. Implementation flaws in transport or application-layer security mechanisms can expose IoT devices to a range of threats, including unauthorized access and data leakage. This paper addresses the ch…

LiFeChain: Lightweight Blockchain for Secure and Efficient Federated Lifelong Learning in IoT
Handi Chen, Jing Deng, Xiuzhe Wu, Zhihan Jiang, Xinchen Zhang, Xianhao Chen, Edith C. H. Ngai
https://arxiv.org/abs/2509.01434

LiFeChain: Lightweight Blockchain for Secure and Efficient Federated Lifelong Learning in IoT
The expansion of Internet of Things (IoT) devices constantly generates heterogeneous data streams, driving demand for continuous, decentralized intelligence. Federated Lifelong Learning (FLL) provides an ideal solution by incorporating federated and lifelong learning to overcome catastrophic forgetting. The extended lifecycle of FLL in IoT systems increases their vulnerability to persistent attacks, and these risks may be obscured by performance degradation caused by spatial-temporal data heter…