Tootfinder

Off-brand IoT devices are still vulnerable to BadBox botnet, FBI says https://therecord.media/iot-devices-vulnerable-to-badbox-botnet-fbi

Spatio-Temporal Information Freshness for Remote Source Monitoring in IoT Systems
Andrea Munari, Federico Chiariotti, Leonardo Badia, Petar Popovski
https://arxiv.org/abs/2506.04804

Spatio-Temporal Information Freshness for Remote Source Monitoring in IoT Systems
The widespread adoption of age of information (AoI) as a meaningful and analytically tractable information freshness metric has led to a wide body of work on the timing performance of Internet of things (IoT) systems. However, the spatial correlation inherent to environmental monitoring has been mostly neglected in the recent literature, due to the significant modeling complexity it introduces. In this work, we address this gap by presenting a model of spatio-temporal information freshness, con…

On The Green Light Signal and Beyond (2021) - Learn how I am trying a smart lighting nudge @home to use 'leccy at grid-friendly times. #IoT #CO2Intensity -

On The Green Light Signal and Beyond (2021)
Learn how I am trying a smart lighting nudge @home to use leccy at grid-friendly times. #IoT #CO2Intensity

In my opinion this router is a real bargain.
cc: @… https://mastodon.social/@bananapi/114815411403617794

Real-Time Monitoring and Transparency in Pizza Production Using IoT and Blockchain
Azmat Ullah, Maria Ilaria Lunesu, Lodovica Marchesi, Roberto Tonelli
https://arxiv.org/abs/2507.02536

Real-Time Monitoring and Transparency in Pizza Production Using IoT and Blockchain
This paper presents a blockchain-based Internet of Things (IoT) system for monitoring pizza production in restaurants. IoT devices track temperature and humidity in real-time, while blockchain ensures secure and tamper-proof data. A Raspberry Pi processes sensor data, captures images, triggers alerts, and interacts with smart contracts. The system detects abnormal conditions, enabling quick responses. Blockchain adds transparency and traceability, supporting compliance and audits. Experiments s…

This https://arxiv.org/abs/2504.09200 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csNI_…

A Datagram Extension to DNS over QUIC: Proven Resource Conservation in the Internet of Things
In this paper, we investigate the Domain Name System (DNS) over QUIC (DoQ) and propose a non-disruptive extension, which can greatly reduce DoQ's resource consumption. This extension can benefit all DNS clients - especially Internet of Things (IoT) devices. This is important because even resource-constrained IoT devices can generate dozens of DNS requests every hour. DNS is a crucial service that correlates IP addresses and domain names. It is traditionally sent as plain-text, favoring low-late…

A Framework for Ethical Judgment of Smart City Applications
Weichen Shi
https://arxiv.org/abs/2506.05172 https://arxiv.org/pdf/2506.0…

A Framework for Ethical Judgment of Smart City Applications
As modern cities increasingly adopt a variety of sensors and Internet of Things (IoT) technologies to collect and analyze data about residents, environments, and public services, they are fostering greater interactions among smart city applications, residents, governments, and businesses. This trend makes it essential for regulators to focus on these interactions to manage smart city practices effectively and prevent unethical outcomes. To facilitate ethical analysis for smart city applications…

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…

No cloud IOT firmware upgrade goes unpunished.
#iot #homeassistant #homeautomation @… @… @…

Evaluating Language Models For Threat Detection in IoT Security Logs
Jorge J. Tejero-Fern\'andez, Alfonso S\'anchez-Maci\'an
https://arxiv.org/abs/2507.02390

Evaluating Language Models For Threat Detection in IoT Security Logs
Log analysis is a relevant research field in cybersecurity as they can provide a source of information for the detection of threats to networks and systems. This paper presents a pipeline to use fine-tuned Large Language Models (LLMs) for anomaly detection and mitigation recommendation using IoT security logs. Utilizing classical machine learning classifiers as a baseline, three open-source LLMs are compared for binary and multiclass anomaly detection, with three strategies: zero-shot, few-shot…

EStacker: Explaining Battery-Less IoT System Performance with Energy Stacks
Lukas Liedtke, Per Gunnar Kjeldsberg, Frank Alexander Kraemer, Magnus Jahre
https://arxiv.org/abs/2505.22366

EStacker: Explaining Battery-Less IoT System Performance with Energy Stacks
The number of Internet of Things (IoT) devices is increasing exponentially, and it is environmentally and economically unsustainable to power all these devices with batteries. The key alternative is energy harvesting, but battery-less IoT systems require extensive evaluation to demonstrate that they are sufficiently performant across the full range of expected operating conditions. IoT developers thus need an evaluation platform that (i) ensures that each evaluated application and configuration…

This https://arxiv.org/abs/2412.07818 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Real-time Chest X-Ray Distributed Decision Support for Resource-constrained Clinics
Internet of Things (IoT) based healthcare systems offer significant potential for improving the delivery of healthcare services in humanitarian engineering, providing essential healthcare services to millions of underserved people in remote areas worldwide. However, these areas have poor network infrastructure, making communications difficult for traditional IoT. This paper presents a real-time chest X-ray classification system for hospitals in remote areas using FastDDS real-time middleware, o…

On the Role of Early-Termination for Age of Information in Tree-Based Random Access Protocols
Andrea Munari, Cedomir Stefanovic
https://arxiv.org/abs/2506.04793

On the Role of Early-Termination for Age of Information in Tree-Based Random Access Protocols
Age of Information (AoI) has emerged as a key metric for assessing data freshness in IoT applications, where a large number of devices report time-stamped updates to a monitor. Such systems often rely on random access protocols based on variations of ALOHA at the link layer, where collision resolution algorithms play a fundamental role to enable reliable delivery of packets. In this context, we provide the first analytical characterization of average AoI for the classical Capetanakis tree-based…

REDUS: Adaptive Resampling for Efficient Deep Learning in Centralized and Federated IoT Networks
Eyad Gad, Gad Gad, Mostafa M. Fouda, Mohamed I. Ibrahem, Muhammad Ismail, Zubair Md Fadlullah
https://arxiv.org/abs/2507.02021

REDUS: Adaptive Resampling for Efficient Deep Learning in Centralized and Federated IoT Networks
With the rise of Software-Defined Networking (SDN) for managing traffic and ensuring seamless operations across interconnected devices, challenges arise when SDN controllers share infrastructure with deep learning (DL) workloads. Resource contention between DL training and SDN operations, especially in latency-sensitive IoT environments, can degrade SDN's responsiveness and compromise network performance. Federated Learning (FL) helps address some of these concerns by decentralizing DL training…

An object-centric core metamodel for IoT-enhanced event logs
Yannis Bertrand, Christian Imenkamp, Lukas Malburg, Matthias Ehrendorfer, Marco Franceschetti, Joscha Gr\"uger, Francesco Leotta, J\"urgen Mangler, Ronny Seiger, Agnes Koschmider, Stefanie Rinderle-Ma, Barbara Weber, Estefania Serral
https://arxiv.org/abs/250…

An object-centric core metamodel for IoT-enhanced event logs
Advances in Internet-of-Things (IoT) technologies have prompted the integration of IoT devices with business processes (BPs) in many organizations across various sectors, such as manufacturing, healthcare and smart spaces. The proliferation of IoT devices leads to the generation of large amounts of IoT data providing a window on the physical context of BPs, which facilitates the discovery of new insights about BPs using process mining (PM) techniques. However, to achieve these benefits, IoT dat…

I remain foxed (pun intended) that Firefox still refuses to connect to an IoT device on my local IPv4 subnet unless that device supports TLS (HTTPS).
And I am further foxed that among the possible reasons for that refusal it does not list the possibility that the local device does not support HTTPS.
Once again I have to revert to another browser to do something that Firefox ought to be able to do (and once was able to do.)

🇺🇦 #NowPlaying on KEXP's #MiddayShow
Aveo:
🎵 The Idiot on the Bike
#Aveo
https://aveo.bandcamp.com/track/the-idiot-on-the-bike

Navigating the Edge-Cloud Continuum: A State-of-Practice Survey
Loris Belcastro, Fabrizio Marozzo, Alessio Orsino, Domenico Talia, Paolo Trunfio
https://arxiv.org/abs/2506.02003

Navigating the Edge-Cloud Continuum: A State-of-Practice Survey
The edge-cloud continuum has emerged as a transformative paradigm that meets the growing demand for low-latency, scalable, end-to-end service delivery by integrating decentralized edge resources with centralized cloud infrastructures. Driven by the exponential growth of IoT-generated data and the need for real-time responsiveness, this continuum features multi-layered architectures. However, its adoption is hindered by infrastructural challenges, fragmented standards, and limited guidance for d…

Nordic Semiconductor acquires US startup Memfault, a cloud-based IoT lifecycle management and observability service that supports secure OTA updates, for $120M (Nick Flaherty/eeNews Europe)
https://www.eenewseurope.com/en/nordic-semi-buys-memfault-for-120m/

Nordic Semi buys Memfault for $120m
Nordic Semiconductor is buying US startup Memfault for $120m for its cloud-based software monitoring platform.

Predictive Control over LAWN: Joint Trajectory Design and Resource Allocation
Haijia Jin, Jun Wu, Weijie Yuan, Ruizhi Ruan, Jiacheng Wang, Dusit Niyato, Dong In Kim, Abbas Jamalipour
https://arxiv.org/abs/2507.02374

Predictive Control over LAWN: Joint Trajectory Design and Resource Allocation
Low-altitude wireless networks (LAWNs) have been envisioned as flexible and transformative platforms for enabling delay-sensitive control applications in Internet of Things (IoT) systems. In this work, we investigate the real-time wireless control over a LAWN system, where an aerial drone is employed to serve multiple mobile automated guided vehicles (AGVs) via finite blocklength (FBL) transmission. Toward this end, we adopt the model predictive control (MPC) to ensure accurate trajectory track…

This https://arxiv.org/abs/2506.00377 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

A Systematic Review of Metaheuristics-Based and Machine Learning-Driven Intrusion Detection Systems in IoT
The widespread adoption of the Internet of Things (IoT) has raised a new challenge for developers since it is prone to known and unknown cyberattacks due to its heterogeneity, flexibility, and close connectivity. To defend against such security breaches, researchers have focused on building sophisticated intrusion detection systems (IDSs) using machine learning (ML) techniques. Although these algorithms notably improve detection performance, they require excessive computing power and resources,…

#Worldrecord: 1 million GB per sec #internet speed achieved by #Japan over 1,100 miles

Japan sends 1 million GB of data across 1,100 miles in a second
Current data transfer speeds aren’t enough to support AI, VR, IoT, and various other emerging technologies. Here’s a mindblowing solution.

B2LoRa: Boosting LoRa Transmission for Satellite-IoT Systems with Blind Coherent Combining
Yimin Zhao, Weibo Wang, Xiong Wang, Linghe Kong, Jiadi Yu, Yifei Zhu, Shiyuan Li, Chong He, Guihai Chen
https://arxiv.org/abs/2505.24140

B2LoRa: Boosting LoRa Transmission for Satellite-IoT Systems with Blind Coherent Combining
With the rapid growth of Low Earth Orbit (LEO) satellite networks, satellite-IoT systems using the LoRa technique have been increasingly deployed to provide widespread Internet services to low-power and low-cost ground devices. However, the long transmission distance and adverse environments from IoT satellites to ground devices pose a huge challenge to link reliability, as evidenced by the measurement results based on our real-world setup. In this paper, we propose a blind coherent combining d…

DCMF: A Dynamic Context Monitoring and Caching Framework for Context Management Platforms
Ashish Manchanda, Prem Prakash Jayaraman, Abhik Banerjee, Kaneez Fizza, Arkady Zaslavsky
https://arxiv.org/abs/2506.17226

DCMF: A Dynamic Context Monitoring and Caching Framework for Context Management Platforms
The rise of context-aware IoT applications has increased the demand for timely and accurate context information. Context is derived by aggregating and inferring from dynamic IoT data, making it highly volatile and posing challenges in maintaining freshness and real-time accessibility. Caching is a potential solution, but traditional policies struggle with the transient nature of context in IoT (e.g., ensuring real-time access for frequent queries or handling fast-changing data). To address this…

This https://arxiv.org/abs/2406.15119 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSD_…

Breaking Resource Barriers in Speech Emotion Recognition via Data Distillation
Speech emotion recognition (SER) plays a crucial role in human-computer interaction. The emergence of edge devices in the Internet of Things (IoT) presents challenges in constructing intricate deep learning models due to constraints in memory and computational resources. Moreover, emotional speech data often contains private information, raising concerns about privacy leakage during the deployment of SER models. To address these challenges, we propose a data distillation framework to facilitate…

Distributed gradient methods under heavy-tailed communication noise
Manojlo Vukovic, Dusan Jakovetic, Dragana Bajovic, Soummya Kar
https://arxiv.org/abs/2505.24464

Distributed gradient methods under heavy-tailed communication noise
We consider a standard distributed optimization problem in which networked nodes collaboratively minimize the sum of their locally known convex costs. For this setting, we address for the first time the fundamental problem of design and analysis of distributed methods to solve the above problem when inter-node communication is subject to \emph{heavy-tailed} noise. Heavy-tailed noise is highly relevant and frequently arises in densely deployed wireless sensor and Internet of Things (IoT) network…

STM32-Based IoT Framework for Real-Time Environmental Monitoring and Wireless Node Synchronization
Ahmed Faizul Haque Dhrubo, Sazid Hasan, Mohammad Abdul Qayum
https://arxiv.org/abs/2506.17295

STM32-Based IoT Framework for Real-Time Environmental Monitoring and Wireless Node Synchronization
The fast pace of technological growth has created a heightened need for intelligent, autonomous monitoring systems in a variety of fields, especially in environmental applications. This project shows the design process and implementation of a proper dual node (master-slave) IoT-based monitoring system using STM32F103C8T6 microcontrollers. The structure of the wireless monitoring system studies the environmental conditions in real-time and can measure parameters like temperature, humidity, soil …

This https://arxiv.org/abs/2504.12849 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

FedX: Adaptive Model Decomposition and Quantization for IoT Federated Learning
Federated Learning (FL) allows collaborative training among multiple devices without data sharing, thus enabling privacy-sensitive applications on mobile or Internet of Things (IoT) devices, such as mobile health and asset tracking. However, designing an FL system with good model utility that works with low computation/communication overhead on heterogeneous, resource-constrained mobile/IoT devices is challenging. To address this problem, this paper proposes FedX, a novel adaptive model decompo…

Lakers, an implementation of #EDHOC, i.e., lightweight security for #IoT, now uses formal verification to continuously check a first small part of its code using #hax and F*, proving our buffers won't reach out of the…

RL-based Adaptive Task Offloading in Mobile-Edge Computing for Future IoT Networks
Ziad Qais Al Abbasi, Khaled M. Rabie, Senior Member, Xingwang Li, Senior Member, Wali Ullah Khan, Asma Abu Samah
https://arxiv.org/abs/2506.22474

RL-based Adaptive Task Offloading in Mobile-Edge Computing for Future IoT Networks
The Internet of Things (IoT) has been increasingly used in our everyday lives as well as in numerous industrial applications. However, due to limitations in computing and power capabilities, IoT devices need to send their respective tasks to cloud service stations that are usually located at far distances. Having to transmit data far distances introduces challenges for services that require low latency such as industrial control in factories and plants as well as artificial intelligence assiste…

GroupNL: Low-Resource and Robust CNN Design over Cloud and Device
Chuntao Ding, Jianhang Xie, Junna Zhang, Salman Raza, Shangguang Wang, Jiannong Cao
https://arxiv.org/abs/2506.12335

GroupNL: Low-Resource and Robust CNN Design over Cloud and Device
It has become mainstream to deploy Convolutional Neural Network (CNN) models on ubiquitous Internet of Things (IoT) devices with the help of the cloud to provide users with a variety of high-quality services. Most existing methods have two limitations: (i) low robustness in handling corrupted image data collected by IoT devices; and (ii) high consumption of computational and transmission resources. To this end, we propose the Grouped NonLinear transformation generation method (GroupNL), which g…

Doppler Estimation and Compensation Techniques in LoRa Direct-to-Satellite Communications
Jamil Farhat, Gianni Pasolini, Enrico Paolini, Muhammad Asad Ullah, Richard Demo Souza
https://arxiv.org/abs/2506.20858

Doppler Estimation and Compensation Techniques in LoRa Direct-to-Satellite Communications
Within the LPWAN framework, the LoRa modulation adopted by LoRaWAN technology has garnered significant interest as a connectivity solution for IoT applications due to its ability to offer low-cost, low-power, and long-range communications. One emerging use case of LoRa is DtS connectivity, which extends coverage to remote areas for supporting IoT operations. The satellite IoT industry mainly prefers LEO because it has lower launch costs and less path loss compared to Geostationary orbit. Howeve…

A Mixed-Signal Photonic SRAM-based High-Speed Energy-Efficient Photonic Tensor Core with Novel Electro-Optic ADC
Md Abdullah-Al Kaiser, Sugeet Sunder, Ajey P. Jacob, Akhilesh R. Jaiswal
https://arxiv.org/abs/2506.22705

A Mixed-Signal Photonic SRAM-based High-Speed Energy-Efficient Photonic Tensor Core with Novel Electro-Optic ADC
The rapid surge in data generated by Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML) applications demands ultra-fast, scalable, and energy-efficient hardware, as traditional von Neumann architectures face significant latency and power challenges due to data transfer bottlenecks between memory and processing units. Furthermore, conventional electrical memory technologies are increasingly constrained by rising bitline and wordline capacitance, as well as the resi…

Innovative Research on IoT Architecture and Robotic Operating Platforms: Applications of Large Language Models and Generative AI
Huiwen Han
https://arxiv.org/abs/2506.22477

Innovative Research on IoT Architecture and Robotic Operating Platforms: Applications of Large Language Models and Generative AI
This paper introduces an innovative design for robotic operating platforms, underpinned by a transformative Internet of Things (IoT) architecture, seamlessly integrating cutting-edge technologies such as large language models (LLMs), generative AI, edge computing, and 5G networks. The proposed platform aims to elevate the intelligence and autonomy of IoT systems and robotics, enabling them to make real-time decisions and adapt dynamically to changing environments. Through a series of compelling…

This https://arxiv.org/abs/2407.02764 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csOS_…

Data-driven Software-based Power Estimation for Embedded Devices
Energy measurement of computer devices, which are widely used in the Internet of Things (IoT), is an important yet challenging task. Most of these IoT devices lack ready-to-use hardware or software for power measurement. In this paper, we propose an easy-to-use approach to derive a software-based energy estimation model with external low-end power meters based on data-driven analysis. Our solution is demonstrated with a Jetson Nano board and Ruideng UM25C USB power meter. Various machine learni…

This https://arxiv.org/abs/2411.17931 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Combining Threat Intelligence with IoT Scanning to Predict Cyber Attack
While the Web has become a global platform for communication, malicious actors, including hackers and hacktivist groups, often disseminate ideological content and coordinate activities through the "Dark Web", an obscure counterpart of the conventional web. Presently, challenges such as information overload and the fragmented nature of cyber threat data impede comprehensive profiling of these actors, thereby limiting the efficacy of predictive analyses of their online activities. Concurrently, t…

Constant Modulus Waveforms for IoT-Centric Integrated Sensing and Communications
Tian Han, Shalanika Dayarathna, Rajitha Senanayake, Peter Smith, Aryan Kaushik, Alain Mourad, Richard A. Stirling-Gallacher, Jamie Evans
https://arxiv.org/abs/2506.21078

Constant Modulus Waveforms for IoT-Centric Integrated Sensing and Communications
Integrated sensing and communications (ISAC) is considered a key enabler to support application scenarios such as the Internet-of-Things (IoT) in which both communications and sensing play significant roles. Multi-carrier waveforms, such as orthogonal frequency division multiplexing (OFDM), have been considered as good candidates for ISAC due to their high communications data rate and good time bandwidth property for sensing. Nevertheless, their high peak-to-average-power-ratio (PAPR) values le…

From Connectivity to Autonomy: The Dawn of Self-Evolving Communication Systems
Zeinab Nezami, Syed Danial Ali Shah, Maryam Hafeez, Karim Djemame, Syed Ali Raza Zaidi
https://arxiv.org/abs/2505.23710

From Connectivity to Autonomy: The Dawn of Self-Evolving Communication Systems
This paper envisions 6G as a self-evolving telecom ecosystem, where AI-driven intelligence enables dynamic adaptation beyond static connectivity. We explore the key enablers of autonomous communication systems, spanning reconfigurable infrastructure, adaptive middleware, and intelligent network functions, alongside multi-agent collaboration for distributed decision-making. We explore how these methodologies align with emerging industrial IoT frameworks, ensuring seamless integration within digi…

On The Green Light Signal and Beyond (2021) - Learn how I am trying a smart lighting nudge @home to use 'leccy at grid-friendly times. #IoT #CO2Intensity -

On The Green Light Signal and Beyond (2021)
Learn how I am trying a smart lighting nudge @home to use leccy at grid-friendly times. #IoT #CO2Intensity

Optimizing Server Load Distribution in Multimedia IoT Environments through LSTM-Based Predictive Algorithms
Somaye Imanpour, Ahmadreza Montazerolghaem, Saeed Afshari
https://arxiv.org/abs/2505.24806

Optimizing Server Load Distribution in Multimedia IoT Environments through LSTM-Based Predictive Algorithms
The Internet of Multimedia Things (IoMT) represents a significant advancement in the evolution of IoT technologies, focusing on the transmission and management of multimedia streams. As the volume of data continues to surge and the number of connected devices grows exponentially, internet traffic has reached unprecedented levels, resulting in challenges such as server overloads and deteriorating service quality. Traditional computer network architectures were not designed to accommodate this ra…

Docs: the FCC is probing USCTM, launched by the Biden administration as a voluntary safety label for IoT devices, over its administrators' alleged ties to China (Brian Flood/Fox News)
https://www.foxnews.com/media/trumps-fcc-p

Trump-appointed FCC chairman probes Biden cybersecurity program over China concerns
President Trump's FCC is raising the alarm over alleged Chinese connections in Biden's cybersecurity labeling initiative as documents reveal national security concerns.

Performance Measurements in the AI-Centric Computing Continuum Systems
Praveen Kumar Donta, Qiyang Zhang, Schahram Dustdar
https://arxiv.org/abs/2506.22884

Performance Measurements in the AI-Centric Computing Continuum Systems
Over the Eight decades, computing paradigms have shifted from large, centralized systems to compact, distributed architectures, leading to the rise of the Distributed Computing Continuum (DCC). In this model, multiple layers such as cloud, edge, Internet of Things (IoT), and mobile platforms work together to support a wide range of applications. Recently, the emergence of Generative AI and large language models has further intensified the demand for computational resources across this continuum…

Adaptive Privacy-Preserving SSD
Na Young Ahn, Dong Hoon Lee
https://arxiv.org/abs/2506.02030 https://arxiv.org/pdf/2506.02030

Adaptive Privacy-Preserving SSD
Data remanence in NAND flash complicates complete deletion on IoT SSDs. We design an adaptive architecture offering four privacy levels (PL0-PL3) that select among address, data, and parity deletion techniques. Quantitative analysis balances efficacy, latency, endurance, and cost. Machine-learning adjusts levels contextually, boosting privacy with negligible performance overhead and complexity.

Development of a Smart Autonomous Irrigation System Using Iot and AI
Yunus Emre Kunt
https://arxiv.org/abs/2506.11835 https://arxiv.o…

Development of a Smart Autonomous Irrigation System Using Iot and AI
Agricultural irrigation ensures that the water required for plant growth is delivered to the soil in a controlled manner. However, uncontrolled management can lead to water waste while reducing agricultural productivity. Drip irrigation systems, which have been one of the most efficient methods since the 1970s, are modernised with IoT and artificial intelligence in this study, aiming to both increase efficiency and prevent water waste. The developed system is designed to be applicable to differ…

Updated #IOT #HomeAssistant #InternetOfTrash @… @… @…

Smart IoT teapot that actually returns HTTP code 418 if you try to make coffee on it

SNR and Resource Adaptive Deep JSCC for Distributed IoT Image Classification
Ali Waqas, Sinem Coleri
https://arxiv.org/abs/2506.10699 https://

SNR and Resource Adaptive Deep JSCC for Distributed IoT Image Classification
Sensor-based local inference at IoT devices faces severe computational limitations, often requiring data transmission over noisy wireless channels for server-side processing. To address this, split-network Deep Neural Network (DNN) based Joint Source-Channel Coding (JSCC) schemes are used to extract and transmit relevant features instead of raw data. However, most existing methods rely on fixed network splits and static configurations, lacking adaptability to varying computational budgets and c…

This https://arxiv.org/abs/2505.21529 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csNI_…

WakeMod: A 6.9uW Wake-Up Radio Module with -72.6dBm Sensitivity for On-Demand IoT
Large-scale Internet of Things (IoT) applications, such as asset tracking and remote sensing, demand multi-year battery lifetimes to minimize maintenance and operational costs. Traditional wireless protocols often employ duty cycling, introducing a tradeoff between latency and idle consumption - both unsuitable for event-driven and ultra-low power systems. A promising approach to address these issues is the integration of always-on wake-up radios (WuRs). They provide asynchronous, ultra-low pow…

Replaced article(s) found for cs.ET. https://arxiv.org/list/cs.ET/new
[1/1]:
- LLM-Empowered IoT for 6G Networks: Architecture, Challenges, and Solutions
Xiaopei Chen, Wen Wu, Liang Li, Fei Ji

On the Role of Color Temperature and Color Rendering Index of White-Light LEDs on the Theoretical Efficiency Limit of Indoor Photovoltaics
Aditi Sharma, Alexander A. Guaman, Jason A. R\"ohr
https://arxiv.org/abs/2506.20811

On the Role of Color Temperature and Color Rendering Index of White-Light LEDs on the Theoretical Efficiency Limit of Indoor Photovoltaics
As the Internet of Things (IoT) continues to grow, the demand for sustainable indoor power sources is increasing. Indoor photovoltaics (IPVs), which are currently in development, present a renewable solution but need to be designed to match specific light sources. While previous studies have emphasized the role of white-light LED color temperature (CT) in determining IPV efficiency and optimum bandgap energy, the role of color rendering index (CRI) remains less understood. In this study, we emp…

TinyML-Based Adaptive Pulse Shaping for Edge Intelligence in IoT/IIoT
Afan Ali
https://arxiv.org/abs/2506.05789 https://arxiv.org/pdf…

TinyML-Based Adaptive Pulse Shaping for Edge Intelligence in IoT/IIoT
Edge intelligence in IoT and IIoT demands lightweight algorithms for data processing on resource-constrained devices. This paper introduces a novel adaptive pulse shape filter based on TinyML for PAPR and SER optimization on edge devices used in uplink IoT communication. Implemented on IoT nodes such as sensors, our pruned neural network provides up to 2 dB PAPR saving over root-raised-cosine (RRC) filters. Mass simulations validate its efficacy in DFT-s-OFDM systems and offer an energy-efficie…

Self-Sustaining Multi-Sensor LoRa-Based Activity Monitoring for Community Workout Parks
Victor Luder, Michele Magno
https://arxiv.org/abs/2506.03203 https:…

Self-Sustaining Multi-Sensor LoRa-Based Activity Monitoring for Community Workout Parks
With the rise of the Internet of Things (IoT), more sensors are deployed around us, covering a wide range of applications from industry and agriculture to urban environments such as smart cities. Throughout these applications the sensors collect data of various characteristics and support city planners and decision-makers in their work processes, ultimately maximizing the impact of public funds. This paper introduces the design and implementation of a self-sustaining wireless sensor node design…

A Language-Agnostic Logical Relation for Message-Passing Protocols
Tesla Zhang, Sonya Simkin, Rui Li, Yue Yao, Stephanie Balzer
https://arxiv.org/abs/2506.10026

A Language-Agnostic Logical Relation for Message-Passing Protocols
Today's computing landscape has been gradually shifting to applications targeting distributed and *heterogeneous* systems, such as cloud computing and Internet of Things (IoT) applications. These applications are predominantly *concurrent*, employ *message-passing*, and interface with *foreign objects*, ranging from externally implemented code to actual physical devices such as sensors. Verifying that the resulting systems adhere to the intended protocol of interaction is challenging -- the usu…

A Systematic Review of Security Vulnerabilities in Smart Home Devices and Mitigation Techniques
Mohammed K. Alzaylaee
https://arxiv.org/abs/2507.01018 http…

A Systematic Review of Security Vulnerabilities in Smart Home Devices and Mitigation Techniques
Smart homes that integrate Internet of Things (IoT) devices face increasing cybersecurity risks, posing significant challenges to these environments. The study explores security threats in smart homes ecosystems, categorizing them into vulnerabilities at the network layer, device level, and those from cloud-based and AI-driven systems. Research findings indicate that post-quantum encryption, coupled with AI-driven anomaly detection, is highly effective in enhancing security; however, computatio…

Energy-Efficient Real-Time Job Mapping and Resource Management in Mobile-Edge Computing
Chuanchao Gao, Niraj Kumar, Arvind Easwaran
https://arxiv.org/abs/2506.12686

Energy-Efficient Real-Time Job Mapping and Resource Management in Mobile-Edge Computing
Mobile-edge computing (MEC) has emerged as a promising paradigm for enabling Internet of Things (IoT) devices to handle computation-intensive jobs. Due to the imperfect parallelization of algorithms for job processing on servers and the impact of IoT device mobility on data communication quality in wireless networks, it is crucial to jointly consider server resource allocation and IoT device mobility during job scheduling to fully benefit from MEC, which is often overlooked in existing studies.…

This https://arxiv.org/abs/2305.03556 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csNI_…

Energy-Latency Aware Intelligent Reflecting Surface Aided Multi-cell Mobile Edge Computing
The explosive development of the Internet of Things (IoT) has led to increased interest in mobile edge computing (MEC), which provides computational resources at network edges to accommodate computation-intensive and latency-sensitive applications. Intelligent reflecting surfaces (IRSs) have gained attention as a solution to overcome blockage problems during the offloading uplink transmission in MEC systems. This paper explores IRS-aided multi-cell networks that enable servers to serve neighbor…

An Efficient Hardware Implementation of Elliptic Curve Point Multiplication over $GF(2^m)$ on FPGA
Ruby Kumari, Tapas Rout, Babul Saini, Jai Gopal Pandey, Abhijit Karmakar
https://arxiv.org/abs/2506.12359

An Efficient Hardware Implementation of Elliptic Curve Point Multiplication over $GF(2^m)$ on FPGA
Elliptic Curve Cryptography (ECC) is widely accepted for ensuring secure data exchange between resource-limited IoT devices. The National Institute of Standards and Technology (NIST) recommended implementation, such as B-163, is particularly well-suited for Internet of Things (IoT) applications. Here, Elliptic Curve Point Multiplication (ECPM) is the most time-critical and resource-intensive operation due to the finite field multiplier. This paper proposes a new implementation method of finite …

Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT
Ioannis Panopoulos, Maria-Lamprini A. Bartsioka, Sokratis Nikolaidis, Stylianos I. Venieris, Dimitra I. Kaklamani, Iakovos S. Venieris
https://arxiv.org/abs/2506.18114

Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT
The rapid expansion of the Internet of Things (IoT) has introduced significant security challenges, necessitating efficient and adaptive Intrusion Detection Systems (IDS). Traditional IDS models often overlook the temporal characteristics of network traffic, limiting their effectiveness in early threat detection. We propose a Transformer-based Early Intrusion Detection System (EIDS) that incorporates dynamic temporal positional encodings to enhance detection accuracy while maintaining computati…

Exploring the Convergence of HCI and Evolving Technologies in Information Systems
Rajan Das Gupta, Ashikur Rahman, Md Imrul Hasan Showmick, Md. Yeasin Rahat, Md. Jakir Hossen
https://arxiv.org/abs/2506.08549

Exploring the Convergence of HCI and Evolving Technologies in Information Systems
Modern technology driven information systems are part of our daily lives. However, this deep integration poses new challenges to the human computer interaction (HCI) professionals. With the rapid growth of mobile and cloud computing and the Internet of Things (IoT), the demand for HCI specialists to design user-friendly and adaptable interfaces has never been more pressing. Especially for diverse user groups such as children, the elderly and people with disabilities who need interfaces tailored…

Coexistence analysis of Wi-Fi 6E and 5G NR-U in the 6 GHz band
Navid Keshtiarast, Marina Petrova
https://arxiv.org/abs/2506.22844 https://

Coexistence analysis of Wi-Fi 6E and 5G NR-U in the 6 GHz band
The ever-increasing demand for broadband and IoT wireless connectivity has recently urged the regulators around the world to start opening the 6 GHz spectrum for unlicensed use. These bands will, for example, permit the use of additional 1.2 GHz in the US and 500 MHz in Europe for unlicensed radio access technologies (RATs) such as Wi-Fi and 5G New Radio Unlicensed (5G NR-U). To support QoS-sensitive applications with both technologies, fair and efficient coexistence approaches between the two …

Joint UAV Trajectory Planning and LEO Satellite Selection for Data Offloading in Space-Air-Ground Integrated Networks
Boran Wang, Ziye Jia, Can Cui, Qihui Wu
https://arxiv.org/abs/2506.12750

Joint UAV Trajectory Planning and LEO Satellite Selection for Data Offloading in Space-Air-Ground Integrated Networks
With the development of low earth orbit (LEO) satellites and unmanned aerial vehicles (UAVs), the space-air-ground integrated network (SAGIN) becomes a major trend in the next-generation networks. However, due to the instability of heterogeneous communication and time-varying characteristics of SAGIN, it is challenging to meet the remote Internet of Things (IoT) demands for data collection and offloading. In this paper, we investigate a two-phase hierarchical data uplink model in SAGIN. Specifi…

Combinatorial Multi-Access Coded Caching with Private Caches under Intersecting Index Constraints
Dhruv Pratap Singh, Anjana A. Mahesh, B. Sundar Rajan
https://arxiv.org/abs/2506.24060

Combinatorial Multi-Access Coded Caching with Private Caches under Intersecting Index Constraints
We consider the coded caching system where each user, equipped with a private cache, accesses a distinct r-subset of access caches. A central server housing a library of files populates both private and access caches using uncoded placement. In this work, we focus on a constrained indexing regime, referred to as the intersection class, in which the sets used to index the demands of each user must have a nonempty intersection. This regime models resource-limited IoT scenarios such as edge-assist…

Cybersecurity Issues in Local Energy Markets
Al Hussein Dabashi, Sajjad Maleki, Biswarup Mukherjee, Gregory Epiphaniou, Carsten Maple, Charalambos Konstantinou, Subhash Lakshminarayana
https://arxiv.org/abs/2507.01536

Cybersecurity Issues in Local Energy Markets
Local Energy Markets (LEMs), though pivotal to the energy transition, face growing cybersecurity threats due to their reliance on smart grid communication standards and vulnerable Internet-of-Things (IoT)-enabled devices. This is a critical issue because such vulnerabilities can be exploited to manipulate market operations, compromise participants' privacy, and destabilize power distribution networks. This work maps LEM communication flows to existing standards, highlights potential impacts of …

G-SEED: A Spatio-temporal Encoding Framework for Forest and Grassland Data Based on GeoSOT
Xuan Ouyang, Xinwen Yu, Yan Chen, Guang Deng, Xuanxin Liu
https://arxiv.org/abs/2506.18094

G-SEED: A Spatio-temporal Encoding Framework for Forest and Grassland Data Based on GeoSOT
In recent years, the rapid development of remote sensing, Unmanned Aerial Vehicles, and IoT technologies has led to an explosive growth in spatio-temporal forest and grassland data, which are increasingly multimodal, heterogeneous, and subject to continuous updates. However, existing Geographic Information Systems (GIS)-based systems struggle to integrate and manage of such large-scale and diverse data sources. To address these challenges, this paper proposes G-SEED (GeoSOT-based Scalable Encod…

E-WAN: Efficient Communication in Energy Harvesting Low-Power Networks
Naomi Stricker, David Blaser, Andres Gomez, Lothar Thiele
https://arxiv.org/abs/2506.23788

E-WAN: Efficient Communication in Energy Harvesting Low-Power Networks
The ever-increasing number of distributed embedded systems in the context of the Internet of Things (IoT), Wireless Sensor Networks (WSN), and Cyber-Physical Systems (CPS) rely on wireless communication to collect and exchange data. Nodes can employ single-hop communication which, despite its ease, may necessitate energy-intensive long-range communication to cover long distances. Conversely, multi-hop communication allows for more energy-efficient short-range communication since nodes can rely …

WakeMod: A 6.9uW Wake-Up Radio Module with -72.6dBm Sensitivity for On-Demand IoT
Lukas Schulthess, Silvano Cortesi, Michele Magno
https://arxiv.org/abs/2505.21529

WakeMod: A 6.9uW Wake-Up Radio Module with -72.6dBm Sensitivity for On-Demand IoT
Large-scale Internet of Things (IoT) applications, such as asset tracking and remote sensing, demand multi-year battery lifetimes to minimize maintenance and operational costs. Traditional wireless protocols often employ duty cycling, introducing a tradeoff between latency and idle consumption - both unsuitable for event-driven and ultra-low power systems. A promising approach to address these issues is the integration of always-on wake-up radios (WuRs). They provide asynchronous, ultra-low pow…

An Efficient Digital Watermarking Technique for Small Scale devices
Kaushik Talathi, Aparna Santra Biswas
https://arxiv.org/abs/2506.06691 https://

An Efficient Digital Watermarking Technique for Small Scale devices
In the age of IoT and mobile platforms, ensuring that content stay authentic whilst avoiding overburdening limited hardware is a key problem. This study introduces hybrid Fast Wavelet Transform & Additive Quantization index Modulation (FWT-AQIM) scheme, a lightweight watermarking approach that secures digital pictures on low-power, memory-constrained small scale devices to achieve a balanced trade-off among robustness, imperceptibility, and computational efficiency. The method embeds watermark …

Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things
Kai Li, Conggai Li, Xin Yuan, Shenghong Li, Sai Zou, Syed Sohail Ahmed, Wei Ni, Dusit Niyato, Abbas Jamalipour, Falko Dressler, Ozgur B. Akan
https://arxiv.org/abs/2505.23792

Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things
This paper focuses on Zero-Trust Foundation Models (ZTFMs), a novel paradigm that embeds zero-trust security principles into the lifecycle of foundation models (FMs) for Internet of Things (IoT) systems. By integrating core tenets, such as continuous verification, least privilege access (LPA), data confidentiality, and behavioral analytics into the design, training, and deployment of FMs, ZTFMs can enable secure, privacy-preserving AI across distributed, heterogeneous, and potentially adversari…

A MARL-based Approach for Easing MAS Organization Engineering
Julien Soul\'e, Jean-Paul Jamont, Michel Occello, Louis-Marie Traonouez, Paul Th\'eron
https://arxiv.org/abs/2506.05437

A MARL-based Approach for Easing MAS Organization Engineering
Multi-Agent Systems (MAS) have been successfully applied in industry for their ability to address complex, distributed problems, especially in IoT-based systems. Their efficiency in achieving given objectives and meeting design requirements is strongly dependent on the MAS organization during the engineering process of an application-specific MAS. To design a MAS that can achieve given goals, available methods rely on the designer's knowledge of the deployment environment. However, high complex…

Reliable Image Transmission in CPS-based Pub/Sub
Everson Flores, Bruna Guterres, Thomaz Pereira Junior, Paula Barros, Alberto Cabral, Cristiana Lima Dora, Marcelo Malheiros, Marcelo Pias
https://arxiv.org/abs/2506.22875

Reliable Image Transmission in CPS-based Pub/Sub
Developments in communication and automation have driven the expansion of distributed networks, essential for IoT and CPS development in industrial applications requiring reliable image processing and real-time adaptability. Although broadly adopted, there is a literature gap regarding the performance of MQTT protocol for image sharing and transmission under high-traffic scenarios with intermittent connectivity, restricting its use in critical IoT and CPS applications. In this context, the pres…

Advances in Small-Footprint Keyword Spotting: A Comprehensive Review of Efficient Models and Algorithms
Soumen Garai, Suman Samui
https://arxiv.org/abs/2506.11169

Advances in Small-Footprint Keyword Spotting: A Comprehensive Review of Efficient Models and Algorithms
Small-Footprint Keyword Spotting (SF-KWS) has gained popularity in today's landscape of smart voice-activated devices, smartphones, and Internet of Things (IoT) applications. This surge is attributed to the advancements in Deep Learning, enabling the identification of predefined words or keywords from a continuous stream of words. To implement the SF-KWS model on edge devices with low power and limited memory in real-world scenarios, a efficient Tiny Machine Learning (TinyML) framework is essen…

Optimizing Indoor RIS-Aided Physical-Layer Security: A Codebook-Generation Methodology and Measurement-Based Analysis
Dimitris Kompostiotis, Dimitris Vordonis, Vassilis Paliouras, George C. Alexandropoulos
https://arxiv.org/abs/2506.22082

Optimizing Indoor RIS-Aided Physical-Layer Security: A Codebook-Generation Methodology and Measurement-Based Analysis
Sixth-Generation (6G) wireless networks aim to support innovative Internet-of-Things (IoT) applications that demand faster and more secure data transmission. While higher Open Systems Interconnection (OSI) layers employ measures like encryption and secure protocols to address data security, Physical-Layer Security (PLS) focuses on preventing information leakage to EavesDroppers (EDs) and mitigating the effects of jammers and spoofing attacks. In this context, the emerging technology of Reconfig…

Client Selection Strategies for Federated Semantic Communications in Heterogeneous IoT Networks
Samer Lahoud, Kinda Khawam
https://arxiv.org/abs/2506.17063

Client Selection Strategies for Federated Semantic Communications in Heterogeneous IoT Networks
The exponential growth of IoT devices presents critical challenges in bandwidth-constrained wireless networks, particularly regarding efficient data transmission and privacy preservation. This paper presents a novel federated semantic communication (SC) framework that enables collaborative training of bandwidth-efficient models for image reconstruction across heterogeneous IoT devices. By leveraging SC principles to transmit only semantic features, our approach dramatically reduces communicatio…

Uhhhh there are sooo many options of this SMLight Zigbee USB adapter thing
SLZB-07
SLZB-07P7
SLZB-07P10
SLZB-07MG24
It’s hard to find information about the differences. Which one is the best? Which of them support both Zigbee and Thread/Matter?
#HomeAssistant #IoT #Zigbee #SmartHome #HomeAutomation

Real-Time Agile Software Management for Edge and Fog Computing Based Smart City Infrastructure
Debasish Jana, Pinakpani Pal, Pawan Kumar
https://arxiv.org/abs/2506.12616

Real-Time Agile Software Management for Edge and Fog Computing Based Smart City Infrastructure
The evolution of smart cities demands scalable, secure, and energy-efficient architectures for real-time data processing. With the number of IoT devices expected to exceed 40 billion by 2030, traditional cloud-based systems are increasingly constrained by bandwidth, latency, and energy limitations. This paper leverages the ROOF (Real-time Onsite Operations Facilitation) framework with decentralized computing at intermediary fog and peripheral edge network layers to reduce latency by processing …

This https://arxiv.org/abs/2501.17707 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csOS_…

vNV-Heap: An Ownership-Based Virtually Non-Volatile Heap for Embedded Systems
The Internet of Batteryless Things might revolutionize our understanding of connected devices by harvesting required operational energy from the environment. These systems come with the system-software challenge that the intermittently powered IoT devices have to checkpoint their state in non-volatile memory to later resume with this state when sufficient energy is available. The scarce energy resources demand that only modified data is persisted before a power failure, which requires precise m…

Leveraging Cloud-Fog Automation for Autonomous Collision Detection and Classification in Intelligent Unmanned Surface Vehicles
Thien Tran, Quang Nguyen, Jonathan Kua, Minh Tran, Toan Luu, Thuong Hoang, Jiong Jin
https://arxiv.org/abs/2506.18024

Leveraging Cloud-Fog Automation for Autonomous Collision Detection and Classification in Intelligent Unmanned Surface Vehicles
Industrial Cyber-Physical Systems (ICPS) technologies are foundational in driving maritime autonomy, particularly for Unmanned Surface Vehicles (USVs). However, onboard computational constraints and communication latency significantly restrict real-time data processing, analysis, and predictive modeling, hence limiting the scalability and responsiveness of maritime ICPS. To overcome these challenges, we propose a distributed Cloud-Edge-IoT architecture tailored for maritime ICPS by leveraging d…

This https://arxiv.org/abs/2501.07148 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Implementing LoRa MIMO System for Internet of Things
Bandwidth constraints limit LoRa implementations. Contemporary IoT applications require higher throughput than that provided by LoRa. This work introduces a LoRa Multiple Input Multiple Output (MIMO) system and a spatial multiplexing algorithm to address LoRa's bandwidth limitation. The transceivers in the proposed approach modulate the signals on distinct frequencies of the same LoRa band. A Frequency Division Multiplexing (FDM) method is used at the transmitters to provide a wider MIMO channe…

Co-Design of Sensing, Communications, and Control for Low-Altitude Wireless Networks
Haijia Jin, Jun Wu, Weijie Yuan, Fan Liu, Yuanhao Cui
https://arxiv.org/abs/2506.20970

Co-Design of Sensing, Communications, and Control for Low-Altitude Wireless Networks
The rapid advancement of Internet of Things (IoT) services and the evolution toward the sixth generation (6G) have positioned unmanned aerial vehicles (UAVs) as critical enablers of low-altitude wireless networks (LAWNs). This work investigates the co-design of integrated sensing, communication, and control ($\mathbf{SC^{2}}$) for multi-UAV cooperative systems with finite blocklength (FBL) transmission. In particular, the UAVs continuously monitor the state of the field robots and transmit thei…

Lightweight and High-Throughput Secure Logging for Internet of Things and Cold Cloud Continuum
Saif E. Nouma, Attila A. Yavuz
https://arxiv.org/abs/2506.08781

Lightweight and High-Throughput Secure Logging for Internet of Things and Cold Cloud Continuum
The growing deployment of resource-limited Internet of Things (IoT) devices and their expanding attack surfaces demand efficient and scalable security mechanisms. System logs are vital for the trust and auditability of IoT, and offloading their maintenance to a Cold Storage-as-a-Service (Cold-STaaS) enhances cost-effectiveness and reliability. However, existing cryptographic logging solutions either burden low-end IoT devices with heavy computation or create verification delays and storage inef…

Unfortunately the #SmartHome #Zigbee #HomeAssistant #IoT #HomeKit

Reinforcement Learning-Based Policy Optimisation For Heterogeneous Radio Access
Anup Mishra, \v{C}edomir Stefanovi\'c, Xiuqiang Xu, Petar Popovski, Israel Leyva-Mayorga
https://arxiv.org/abs/2506.15273

Reinforcement Learning-Based Policy Optimisation For Heterogeneous Radio Access
Flexible and efficient wireless resource sharing across heterogeneous services is a key objective for future wireless networks. In this context, we investigate the performance of a system where latency-constrained internet-of-things (IoT) devices coexist with a broadband user. The base station adopts a grant-free access framework to manage resource allocation, either through orthogonal radio access network (RAN) slicing or by allowing shared access between services. For the IoT users, we propos…

Poster: Enhancing GNN Robustness for Network Intrusion Detection via Agent-based Analysis
Zhonghao Zhan, Huichi Zhou, Hamed Haddadi
https://arxiv.org/abs/2506.20806

Poster: Enhancing GNN Robustness for Network Intrusion Detection via Agent-based Analysis
Graph Neural Networks (GNNs) show great promise for Network Intrusion Detection Systems (NIDS), particularly in IoT environments, but suffer performance degradation due to distribution drift and lack robustness against realistic adversarial attacks. Current robustness evaluations often rely on unrealistic synthetic perturbations and lack demonstrations on systematic analysis of different kinds of adversarial attack, which encompass both black-box and white-box scenarios. This work proposes a no…

A Contemporary Survey on Fluid Antenna Systems: Fundamentals and Networking Perspectives
Hanjiang Hong, Kai-Kit Wong, Hao Xu, Xinghao Guo, Farshad Rostami Ghadi, Yu Chen, Yin Xu, Chan-Byoung Chae, Baiyang Liu, Kin-Fai Tong, Yangyang Zhang
https://arxiv.org/abs/2506.13317

A Contemporary Survey on Fluid Antenna Systems: Fundamentals and Networking Perspectives
The explosive growth of teletraffic, fueled by the convergence of cyber-physical systems and data-intensive applications, such as the Internet of Things (IoT), autonomous systems, and immersive communications, demands a multidisciplinary suite of innovative solutions across the physical and network layers. Fluid antenna systems (FAS) represent a transformative advancement in antenna design, offering enhanced spatial degrees of freedom through dynamic reconfigurability. By exploiting spatial fle…

Generative AI for Vulnerability Detection in 6G Wireless Networks: Advances, Case Study, and Future Directions
Shuo Yang, Xinran Zheng, Jinfeng Xu, Jinze Li, Danyang Song, Zheyu Chen, Edith C. H. Ngai
https://arxiv.org/abs/2506.20488

Generative AI for Vulnerability Detection in 6G Wireless Networks: Advances, Case Study, and Future Directions
The rapid advancement of 6G wireless networks, IoT, and edge computing has significantly expanded the cyberattack surface, necessitating more intelligent and adaptive vulnerability detection mechanisms. Traditional security methods, while foundational, struggle with zero-day exploits, adversarial threats, and context-dependent vulnerabilities in highly dynamic network environments. Generative AI (GAI) emerges as a transformative solution, leveraging synthetic data generation, multimodal reasoni…

Not all those who drift are lost: Drift correction and calibration scheduling for the IoT
Aaron Hurst, Andrey V. Kalinichev, Klaus Koren, Daniel E. Lucani
https://arxiv.org/abs/2506.09186

Not all those who drift are lost: Drift correction and calibration scheduling for the IoT
Sensors provide a vital source of data that link digital systems with the physical world. However, as sensors age, the relationship between what they measure and what they output changes. This is known as sensor drift and poses a significant challenge that, combined with limited opportunity for re-calibration, can severely limit data quality over time. Previous approaches to drift correction typically require large volumes of ground truth data and do not consider measurement or prediction uncer…

Automating Multi-Tenancy Performance Evaluation on Edge Compute Nodes
Joanna Georgiou, Moysis Symeonides, George Pallis, Marios D. Dikaiakos
https://arxiv.org/abs/2506.10461

Automating Multi-Tenancy Performance Evaluation on Edge Compute Nodes
Edge Computing emerges as a promising alternative of Cloud Computing, with scalable compute resources and services deployed in the path between IoT devices and Cloud. Since virtualization techniques can be applied on Edge compute nodes, administrators can share their Edge infrastructures among multiple users, providing the so-called multi-tenancy. Even though multi-tenancy is unavoidable, it raises concerns about security and performance degradation due to resource contention in Edge Computing.…

Hybrid Learning for Cold-Start-Aware Microservice Scheduling in Dynamic Edge Environments
Jingxi Lu, Wenhao Li, Jianxiong Guo, Xingjian Ding, Zhiqing Tang, Tian Wang, Weijia Jia
https://arxiv.org/abs/2505.22424

Hybrid Learning for Cold-Start-Aware Microservice Scheduling in Dynamic Edge Environments
With the rapid growth of IoT devices and their diverse workloads, container-based microservices deployed at edge nodes have become a lightweight and scalable solution. However, existing microservice scheduling algorithms often assume static resource availability, which is unrealistic when multiple containers are assigned to an edge node. Besides, containers suffer from cold-start inefficiencies during early-stage training in currently popular reinforcement learning (RL) algorithms. In this pape…

Physical Layer Challenge-Response Authentication between Ambient Backscatter Devices
Yifan Zhang, Yongchao Dang, Masoud Kaveh, Zheng Yan, Riku J\"antti, Zhu Han
https://arxiv.org/abs/2506.18767

Physical Layer Challenge-Response Authentication between Ambient Backscatter Devices
Ambient backscatter communication (AmBC) has become an integral part of ubiquitous Internet of Things (IoT) applications due to its energy-harvesting capabilities and ultra-low-power consumption. However, the open wireless environment exposes AmBC systems to various attacks, and existing authentication methods cannot be implemented between resource-constrained backscatter devices (BDs) due to their high computational demands.To this end, this paper proposes PLCRA-BD, a novel physical layer chal…

Prospects and challenges of Bluetooth backscatters system
Jingyun Du
https://arxiv.org/abs/2505.21526 https://arxiv.org/pdf/2505.2152…

Prospects and challenges of Bluetooth backscatters system
Bluetooth backscatter systems, as a crucial technology for low-power communication in the Internet of Things (IoT), have witnessed remarkable development in recent years. This article comprehensively analyzes multiple related papers, including the latest advancements in RF-Transformer and B2Loc systems, summarizes their research progress, challenges faced, and classification, and explores the application prospects and future development directions of such systems. Bluetooth backscatter systems …

Automated Energy Billing with Blockchain and the Prophet Forecasting Model: A Holistic Approach
Ajesh Thangaraj Nadar, Soham Chandane, Gabriel Nixon Raj, Nihar Mahesh Pasi, Yash Arvind Patil
https://arxiv.org/abs/2506.16649

Automated Energy Billing with Blockchain and the Prophet Forecasting Model: A Holistic Approach
This paper presents a comprehensive approach to automated energy billing that leverages IoT-based smart meters, blockchain technology, and the Prophet time series forecasting model. The proposed system facilitates real-time power consumption monitoring via Wi-Fi-enabled ESP32 modules and a mobile application interface. It integrates Firebase and blockchain for secure, transparent billing processes and employs smart contracts for automated payments. The Prophet model is used for energy demand fo…

Toward a Lightweight, Scalable, and Parallel Secure Encryption Engine
Rasha Karakchi, Rye Stahle-Smith, Nishant Chinnasami, Tiffany Yu
https://arxiv.org/abs/2506.15070

Toward a Lightweight, Scalable, and Parallel Secure Encryption Engine
The exponential growth of Internet of Things (IoT) applications has intensified the demand for efficient, high-throughput, and energy-efficient data processing at the edge. Conventional CPU-centric encryption methods suffer from performance bottlenecks and excessive data movement, especially in latency-sensitive and resource-constrained environments. In this paper, we present SPiME, a lightweight, scalable, and FPGA-compatible Secure Processor-in-Memory Encryption architecture that integrates t…

VReaves: Eavesdropping on Virtual Reality App Identity and Activity via Electromagnetic Side Channels
Sun Wei, Fang Minghong, Li Mengyuan
https://arxiv.org/abs/2506.17570

VReaves: Eavesdropping on Virtual Reality App Identity and Activity via Electromagnetic Side Channels
Virtual reality (VR) has recently proliferated significantly, consisting of headsets or head-mounted displays (HMDs) and hand controllers for an embodied and immersive experience. The VR device is usually embedded with different kinds of IoT sensors, such as cameras, microphones, communication sensors, etc. However, VR security has not been scrutinized from a physical hardware point of view, especially electromagnetic emanations (EM) that are automatically and unintentionally emitted from the V…

This https://arxiv.org/abs/2501.02469 has been replaced.
link: https://scholar.google.com/scholar?q=a

LoRaConnect: Unlocking HTTP Potential on LoRa Backbones for Remote Areas and Ad-Hoc Networks
The minimal infrastructure requirements of LoRa make it suitable for deployments in remote and disaster-stricken areas. Concomitantly, the modern era is witnessing the proliferation of web applications in all aspects of human life, including IoT and other network services. Contemporary IoT and network solutions heavily rely on web applications to render services. However, despite the recent research and development pivoted around LoRa, there is still a lack of studies focusing on web applicatio…

Physical Layer-Based Device Fingerprinting for Wireless Security: From Theory to Practice
Junqing Zhang, Francesco Ardizzon, Mattia Piana, Guanxiong Shen, Stefano Tomasin
https://arxiv.org/abs/2506.09807

Physical Layer-Based Device Fingerprinting for Wireless Security: From Theory to Practice
The identification of the devices from which a message is received is part of security mechanisms to ensure authentication in wireless communications. Conventional authentication approaches are cryptography-based, which, however, are usually computationally expensive and not adequate in the Internet of Things (IoT), where devices tend to be low-cost and with limited resources. This paper provides a comprehensive survey of physical layer-based device fingerprinting, which is an emerging device a…

The Trip to ZigBee Backscatter across a Decade, a Systematic Review
Yang Liu
https://arxiv.org/abs/2506.13822 https://arxiv.org/pdf/2…

The Trip to ZigBee Backscatter across a Decade, a Systematic Review
The field of backscatter communication has undergone a profound transformation, evolving from a niche technology for radio-frequency identification (RFID) into a sophisticated paradigm poised to enable a truly battery-free Internet of Things (IoT). This evolution is built upon a deepening understanding of the fundamental principles governing these ultra-low-power links. Modern backscatter systems are no longer simple reflectors of continuous waves but are increasingly designed to interact with …

This https://arxiv.org/abs/2410.16316 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

A Computational Harmonic Detection Algorithm to Detect Data Leakage through EM Emanation
Unintended electromagnetic emissions, called EM emanations, can be exploited to recover sensitive information, posing security risks. Metal shielding, used by defense organizations to prevent data leakage, is costly and impractical for widespread use. This issue is particularly significant for IoT devices due to their sheer volume and varied deployment environments. Therefore, there is a research need for an automated detection method to monitor facilities and address data leakage promptly. To …

Efficient Traffic Classification using HW-NAS: Advanced Analysis and Optimization for Cybersecurity on Resource-Constrained Devices
Adel Chehade, Edoardo Ragusa, Paolo Gastaldo, Rodolfo Zunino
https://arxiv.org/abs/2506.11319

Efficient Traffic Classification using HW-NAS: Advanced Analysis and Optimization for Cybersecurity on Resource-Constrained Devices
This paper presents a hardware-efficient deep neural network (DNN), optimized through hardware-aware neural architecture search (HW-NAS); the DNN supports the classification of session-level encrypted traffic on resource-constrained Internet of Things (IoT) and edge devices. Thanks to HW-NAS, a 1D convolutional neural network (CNN) is tailored on the ISCX VPN-nonVPN dataset to meet strict memory and computational limits while achieving robust performance. The optimized model attains an accuracy…

This https://arxiv.org/abs/2501.03465 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csNI_…

Extending Internet Access Over LoRa for Internet of Things and Critical Applications
LoRa bridges the gap between remote locations and mainstream networks, enabling large-scale Internet of Things (IoT) deployments. Despite the recent advancements around LoRa, Internet access over this technology is still largely unexplored. Most existing solutions only handle packets within the local LoRa network and do not interact with web applications. This limits the scalability and the ability to deliver essential web services in disconnected regions. This work proposes and implements ILoR…