Category
1,407 papers
RoPA Manager, a system for automated RoPA information extraction using hybrid retrieval that combines lexical ranking over tsvector, dense-vector search, Reciprocal Rank Fusion (RRF), and locally deployed LLMs, is proposed.
Precise interference detection and identification are crucial for enhancing the survivability of communication systems in non-cooperative wireless environments. While deep learning (DL) has advanced this field, existing single-task learning (STL) approaches neglect inherent task correlations. Furthermore, emerging mult...
Experimental results demonstrate that ForgetMimic effectively eliminates memory of designated motions while maintaining the normal operation of all other motions, and identifies and resolves two key training mechanisms in robot control that lead to unlearning failure.
A robust, lightweight machine learning model featuring LightGBM classifier with SMOTE oversampling and SOM-US undersampling techniques for data balancing, as well as well-engineered feature selection through Genetic Algorithm is proposed, demonstrating a significant enhancement in terms of accuracy from the current sta...
Reach audiences
Advertise in front of researchers, engineers, and readers.
This work introduces ChronosAttack, a delay-only scheduling attack that changes when authentic tool responses arrive without modifying, adding, removing, or accelerating them, to show that tool-response timing can itself form an attack surface in asynchronous LLM agents.
This work investigates combining Federated Learning with TinyML-based model compression for intrusion detection in IoT environments and preliminary results show that training stability plays a critical role in federated TinyML systems.
With recent advancements in large language models (LLMs) and LLM-based agents, these agents are becoming increasingly autonomous and gaining broader access to act on users'behalf on the internet. However, the vulnerability of automated agents deployed on social media platforms (e.g., for managing a user's personal acco...
Real-time payment fraud detection is a non-stationary streaming prediction problem: adversaries adapt before supervised labels mature, and localized burst attacks can cause losses before retraining. Production systems typically rely on tabular classifiers and rules, which can struggle to capture these emerging sequenti...
Three phases and a common pattern in rule engineering are identified, offering SOC managers insights to improve their processes and expectations of engineer expertise, and challenges in generalizing rules beyond available tests are observed.
The tremendous commercial potential of large language models (LLMs) has heightened concerns over their unauthorized use. To address this, we focus on the task of identifying the origin of black-box LLMs. We further propose PlugAE, an effective and efficient identification method that proactively leverages LLM-specific...
This work develops a method for optimizing the auditor's canary set to improve privacy auditing, leveraging recent work on metagradient optimization and demonstrates that in certain instances, using such optimized canaries can improve empirical lower bounds for differentially private image classification models by seve...
HYDRA (Hybrid Drift Adaptation), a proactive adaptation framework that learns drift-invariant representations from hierarchically structured data, unifies feature learning and domain alignment, eliminating the need for complex adversarial objectives.
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.
GPT-Lab
· gpt-lab.eu
Oct 30, 2026
Critical flaws, compromised release channels and agentic AI threats landed within days of each other in mid-October 2026. Why “Black October” may say more about how well we now find weaknesses than about the attacks themselves. The post Black October? The Week AI Changed the Cybersecurity Conversation appeared first on GPT-Lab.
Gemini 4 Carbon is our strongest model with state-of-the-art cybersecurity and long horizon capabilities.
Gemini 3.8 Flash and 3.8 Flash Cyber deliver next-generation intelligence for agentic workflows and cybersecurity.
Google introduces Gemini 3.5 Flash Cyber, a lightweight cybersecurity model to find and patch vulnerabilities.
Students from the MIT Cybersecurity Clinic help local governments and other vulnerable organizations defend against digital threats.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
