Tootfinder

Security — A data breach at analytics giant Mixpanel leaves a lot of open questions
A cybersecurity incident at analytics provider Mixpanel announced just hours before the U.S. Thanksgiving holiday weekend could set a new standard for how not to announce a data breach.
📍 https://

A data breach at analytics giant Mixpanel leaves a lot of open questions | TechCrunch
We sent over a dozen questions to Mixpanel's CEO about the company's data breach. Here's what we want to know.

Absolutely the worst thing about having *finally* built myself the analytics dashboard I wanted for my winter-time cycling data is that I'm going to spend too long looking at data and not enough time generating data, i.e., actually riding my bike. )-:

Bogus #BGP routes that were little noticed. The origin ASN appears to have been a typo for #AS327885 (Viettel Tanzania), perhaps in a failed attempt at a government directed shutdown?

OpenAI discloses API customer data breach via Mixpanel vendor hack
Mixpanel reported that the attack “impacted a limited number of our customers” and resulted from a smishing (SMS phishing) campaign that the company detected on November 8.
OpenAI received details of the affected dataset on November 25 after being informed of Mixpanel’s ongoing investigation.
The AI company notes that the exposed information may include:

• Name that was provided to …

OpenAI discloses API customer data breach via Mixpanel vendor hack
OpenAI is notifying some ChatGPT API customers that limited identifying information was exposed following a breach at its third-party analytics provider Mixpanel.

Crypto media company Blockworks is closing its newsroom, launched in 2021, and will focus on software and data, continuing its main newsletters and podcasts (Pooja Rajkumari/TheStreet)
https://www.thestreet.com/crypto/jobs/blockworks-s…

そういえばTootleについて、危険であるという指摘もありましたね。
謎にクリップボードアクセスしていること、Google Analytics for Firebaseで行動追跡情報を収集していること、それらのプライバシーポリシー（収集範囲や用途制限の宣言）が公開されていないこと、かな。通知をリレーするサーバが情報収集しやすいという話もあります。
こちらに収集している情報のjsonとか書いておきました。
https://

COSTAR-A: A prompting framework for enhancing Large Language Model performance on Point-of-View questions
Nzubechukwu C. Ohalete (School of Data Science and Analytics, Kennesaw State University, GA, USA), Kevin B. Gittner (School of Data Science and Analytics, Kennesaw State University, GA, USA), Lauren M. Matheny (School of Data Science and Analytics, Kennesaw State University, GA, USA)

COSTAR-A: A prompting framework for enhancing Large Language Model performance on Point-of-View questions
Large Language Models (LLMs) are highly sensitive to prompt design, and making optimized prompting techniques is crucial for generating consistent, high-quality outputs. In this study, we introduce COSTAR-A, a novel prompt engineering framework that enhances the existing COSTAR method, which stands for Context, Objective, Style, Tone, Audience, and Response, by adding the 'Answer' component at the end. We demonstrate that while the original COSTAR framework improves prompt clarity and aligns ou…

Spiral Model Technique For Data Science & Machine Learning Lifecycle
Rohith Mahadevan
https://arxiv.org/abs/2510.06987 https://arxiv.org/pdf/2510.06987…

Spiral Model Technique For Data Science & Machine Learning Lifecycle
Analytics play an important role in modern business. Companies adapt data science lifecycles to their culture to seek productivity and improve their competitiveness among others. Data science lifecycles are fairly an important contributing factor to start and end a project that are data dependent. Data science and Machine learning life cycles comprises of series of steps that are involved in a project. A typical life cycle states that it is a linear or cyclical model that revolves around. It is…

Numeric, which automates accounting workflows, raised a $51M Series B led by IVP, bringing its total funding to $89M, and says OpenAI and Brex are clients (Ryan Lawler/Axios)
https://www.axios.com/pro/fintech-deals/2025/11/19/numeric-51-million-acc…

Exclusive: Numeric raises $51M to automate accounting
Company connects close, cash and analytics in one data layer.

i am assigned to two exam committees for january prelims, one on energy-efficient model training and the other on i/o-compute balance in GPU-based data analytics. yummy.

Real-Time Health Analytics Using Ontology-Driven Complex Event Processing and LLM Reasoning: A Tuberculosis Case Study
Ritesh Chandra, Sonali Agarwal, Navjot Singh
https://arxiv.org/abs/2510.09646

Real-Time Health Analytics Using Ontology-Driven Complex Event Processing and LLM Reasoning: A Tuberculosis Case Study
Timely detection of critical health conditions remains a major challenge in public health analytics, especially in Big Data environments characterized by high volume, rapid velocity, and diverse variety of clinical data. This study presents an ontology-enabled real-time analytics framework that integrates Complex Event Processing (CEP) and Large Language Models (LLMs) to enable intelligent health event detection and semantic reasoning over heterogeneous, high-velocity health data streams. The a…

Embodied Natural Language Interaction (NLI): Speech Input Patterns in Immersive Analytics
Hyemi Song, Matthew Johnson, Kirsten Whitley, Eric Krokos, Amitabh Varshney
https://arxiv.org/abs/2510.12156

Embodied Natural Language Interaction (NLI): Speech Input Patterns in Immersive Analytics
Embodiment shapes how users verbally express intent when interacting with data through speech interfaces in immersive analytics. Despite growing interest in Natural Language Interaction (NLI) for visual analytics in immersive environments, users' speech patterns and their use of embodiment cues in speech remain underexplored. Understanding their interplay is crucial to bridging the gap between users' intent and an immersive analytic system. To address this, we report the results from 15 partici…

Prepared for the Unknown: Adapting AIOps Capacity Forecasting Models to Data Changes
Lorena Poenaru-Olaru, Wouter van 't Hof, Adrian Stando, Arkadiusz P. Trawinski, Eileen Kapel, Jan S. Rellermeyer, Luis Cruz, Arie van Deursen
https://arxiv.org/abs/2510.10320

Prepared for the Unknown: Adapting AIOps Capacity Forecasting Models to Data Changes
Capacity management is critical for software organizations to allocate resources effectively and meet operational demands. An important step in capacity management is predicting future resource needs often relies on data-driven analytics and machine learning (ML) forecasting models, which require frequent retraining to stay relevant as data evolves. Continuously retraining the forecasting models can be expensive and difficult to scale, posing a challenge for engineering teams tasked with balanc…

Federated Data Analytics for Cancer Immunotherapy: A Privacy-Preserving Collaborative Platform for Patient Management
Mira Raheem, Michael Papazoglou, Bernd Kr\"amer, Neamat El-Tazi, Amal Elgammal
https://arxiv.org/abs/2510.09155

Federated Data Analytics for Cancer Immunotherapy: A Privacy-Preserving Collaborative Platform for Patient Management
Connected health is a multidisciplinary approach focused on health management, prioritizing pa-tient needs in the creation of tools, services, and treatments. This paradigm ensures proactive and efficient care by facilitating the timely exchange of accurate patient information among all stake-holders in the care continuum. The rise of digital technologies and process innovations promises to enhance connected health by integrating various healthcare data sources. This integration aims to persona…

Millions impacted by PornHub, SoundCloud data breaches https://therecord.media/millions-impacted-pornhub-soundcloud-breaches

MobilityDuck: Mobility Data Management with DuckDB
Nhu Ngoc Hoang, Ngoc Hoa Pham, Viet Phuong Hoang, Esteban Zim\'anyi
https://arxiv.org/abs/2510.07963 https://

MobilityDuck: Mobility Data Management with DuckDB
The analytics of spatiotemporal data is increasingly important for mobility analytics. Despite extensive research on moving object databases (MODs), few systems are ready on production or lightweight enough for analytics. MobilityDB is a notable system that extends PostgreSQL with spatiotemporal data, but it inherits complexity of the architecture as well. In this paper, we present MobilityDuck, a DuckDB extension that integrates the MEOS library to provide support spatiotemporal and other temp…

Alembic, which offers AI-powered data analytics for marketers, raised a $145M Series B led by Prysm and Accenture at a $645M valuation, up from $49M in 2024 (Patrick Coffee/Wall Street Journal)
https://www.wsj.com/articles/accenture-and

📈 #LogsQL query language provides fast full-text search, advanced analytics, and data extraction/transformation at query time. Can be combined with Unix tools like grep, less, sort, and jq for log analysis.
🎯 Optimized for high cardinality fields like trace_id, user_id, and ip addresses. Supports logs with hundreds of fields (wide events), multitenancy, out-of-order ingestion, live taili…

Parrot Analytics: movies made up ~50% of streaming revenue across Netflix, Prime Video, Disney , and WBD in 2024, up from ~27% in 2022, based on engagement data (Alejandro Rojas/The Hollywood Reporter)
https://www.hollywoodreporter.com/business/b…

How Movies Increasingly Drive Streaming Revenue
A Parrot Analytics analysis of thousands of titles across Amazon Prime Video, Disney+, Netflix, and Max finds that movies deliver disproportionately high engagement relative to the volume of content hours they represent.

Human-Centered Development of Indicators for Self-Service Learning Analytics: A Transparency through Exploration Approach
Shoeb Joarder, Mohamed Amine Chatti
https://arxiv.org/abs/2510.08395

Human-Centered Development of Indicators for Self-Service Learning Analytics: A Transparency through Exploration Approach
The aim of learning analytics is to turn educational data into insights, decisions, and actions to improve learning and teaching. The reasoning of the provided insights, decisions, and actions is often not transparent to the end-user, and this can lead to trust and acceptance issues when interventions, feedback, and recommendations fail. In this paper, we shed light on achieving transparent learning analytics by following a transparency through exploration approach. To this end, we present the …

VisPile: A Visual Analytics System for Analyzing Multiple Text Documents With Large Language Models and Knowledge Graphs
Adam Coscia, Alex Endert
https://arxiv.org/abs/2510.09605

VisPile: A Visual Analytics System for Analyzing Multiple Text Documents With Large Language Models and Knowledge Graphs
Intelligence analysts perform sensemaking over collections of documents using various visual and analytic techniques to gain insights from large amounts of text. As data scales grow, our work explores how to leverage two AI technologies, large language models (LLMs) and knowledge graphs (KGs), in a visual text analysis tool, enhancing sensemaking and helping analysts keep pace. Collaborating with intelligence community experts, we developed a visual analytics system called VisPile. VisPile inte…

Slicing Is All You Need: Towards A Universal One-Sided Algorithm for Distributed Matrix Multiplication
Benjamin Brock, Renato Golin
https://arxiv.org/abs/2510.08874 https://

Slicing Is All You Need: Towards A Universal One-Sided Algorithm for Distributed Matrix Multiplication
Many important applications across science, data analytics, and AI workloads depend on distributed matrix multiplication. Prior work has developed a large array of algorithms suitable for different problem sizes and partitionings including 1D, 2D, 1.5D, and 2.5D algorithms. A limitation of current work is that existing algorithms are limited to a subset of partitionings. Multiple algorithm implementations are required to support the full space of possible partitionings. If no algorithm implemen…

Edge-to-Cloud Computations-as-a-Service in Software-Defined Energy Networks for Smart Grids
Jack Jackman, David Ryan, Arun Narayanan, Pedro Nardelli, Indrakshi Dey
https://arxiv.org/abs/2510.11286

Edge-to-Cloud Computations-as-a-Service in Software-Defined Energy Networks for Smart Grids
Modern power grids face an acute mismatch between where data is generated and where it can be processed: protection relays, EV (Electric Vehicle) charging, and distributed renewables demand millisecond analytics at the edge, while energy-hungry workloads often sit in distant clouds leading to missed real-time deadlines and wasted power. We address this by proposing, to our knowledge, the first-ever SDEN (Software Defined Energy Network) for CaaS (Computations-as-a-Service) that unifies edge, fo…

Cumulus Media sues Nielsen, accusing it of anticompetitive moves by requiring the purchase of local radio ratings data in order to access its national analytics (Mike Scarcella/Reuters)
https://www.reuters.com/legal/litigation/r

The Virginia Community College System (#AS22845) had long been announcing two IPv4 prefixes, a /16 and a /24. Most of the /16 has now been disaggregated.
A variety of explanations could account for such a major change, such as:
1. Operational mistake
2. Prelude to re-allocate or transfer
3. Traffic engineering
4. DDoS mitigation

Interplay between Security, Privacy and Trust in 6G-enabled Intelligent Transportation Systems
Ahmed Danladi Abdullahi, Erfan Bahrami, Tooska Dargahi, Mohammed Al-Khalidi, Mohammad Hammoudeh
https://arxiv.org/abs/2510.02487

Interplay between Security, Privacy and Trust in 6G-enabled Intelligent Transportation Systems
The advancement of 6G technology has the potential to revolutionize the transportation sector and significantly improve how we travel. 6G-enabled Intelligent Transportation Systems (ITS) promise to offer high-speed, low-latency communication and advanced data analytics capabilities, supporting the development of safer, more efficient, and more sustainable transportation solutions. However, various security and privacy challenges were identified in the literature that must be addressed to enable…

Unveiling Gamer Archetypes through Multi modal feature Correlations and Unsupervised Learning
Moona Kanwal, Muhammad Sami Siddiqui, Syed Anael Ali
https://arxiv.org/abs/2510.10263

Unveiling Gamer Archetypes through Multi modal feature Correlations and Unsupervised Learning
Profiling gamers provides critical insights for adaptive game design, behavioral understanding, and digital well-being. This study proposes an integrated, data-driven framework that combines psychological measures, behavioral analytics, and machine learning to reveal underlying gamer personas. A structured survey of 250 participants, including 113 active gamers, captured multidimensional behavioral, motivational, and social data. The analysis pipeline integrated feature engineering, association…

A LoRa IoT Framework with Machine Learning for Remote Livestock Monitoring in Smart Agriculture
Hitesh Mohapatra
https://arxiv.org/abs/2510.07322 https://a…

A LoRa IoT Framework with Machine Learning for Remote Livestock Monitoring in Smart Agriculture
This work presents AgroTrack, a LoRa-based IoT framework for remote livestock monitoring in smart agriculture. The system is designed for low-power, long-range communication and supports real-time tracking and basic health assessment of free-range livestock through GPS, motion, and temperature sensors integrated into wearable collars. Data is collected and transmitted via LoRa to gateways and forwarded to a cloud platform for visualization, alerts, and analytics. To enhance its practical deploy…