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1,407 papers
This work derives Renyi-DP guarantees separating privacy leakage through the posterior mean from a distinct channel induced by the data-dependent posterior covariance, and identifies effective ridge regularisation and covariance scale as the principal privacy-controlling quantities.
As a critical application of computational intelligence in remote sensing, deep learning-based synthetic aperture radar (SAR) image target recognition facilitates intelligent perception but typically relies on centralized training, where multi-source SAR data are uploaded to a single server, raising privacy and securit...
Machine learning models are increasingly deployed in healthcare imaging pipelines for diagnostic support, and training-time attacks against them are a named sector-level concern: healthcare-sector guidance identifies model poisoning and adversarial attacks as threats requiring dedicated defenses, while federal policy d...
EI-DDLGN is presented, the first in-depth study of TFHE-based DDLGN inference, and how encrypted execution cost depends on model size, learned Boolean-function distribution, and propagated wire status is characterized, and Model-Fixed-Wire PBS Bypass (MFW-PBS Bypass), a semantics-preserving execution strategy that elim...
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CanAL, a closed-form water-filling allocation that gives important channels proportionally less noise, is derived and it is proved it strictly minimizes importance-weighted distortion at a fixed budget.
DualView deterministically prevents instructions in untrusted data from directly steering the agent's tool calls from directly steering the agent's tool calls; this guarantee does not depend on recognizing the evaluated attack templates.
This new Semantic Gambit attack overcomes this causal limitation by augmenting the adversary with predictive context derived from a Large Language Model in real-time by augmenting the adversary with predictive context derived from a Large Language Model in real-time.
IntraGuard is proposed, a black-box, venue-agnostic defense framework grounded in the structural--visual decoupling inherent to the PDF that achieves a defense success rate of up to 84%, while preserving peer-review invariance for human reviewers.
This paper presents GAAP (Guaranteed Accounting for Agent Privacy), an execution environment for AI agents that guarantees confidentiality for private user data deterministically, without trusting the agent with private user data, and without requiring any AI model or the user prompt to be free of attacks.
This paper designs a realistic and controlled experimental environment, evaluating 33 CVEs across 20 real-world projects and two popular ACR pipelines, to assess the susceptibility of real-world ACR pipelines to vulnerability re-introduction attacks and finds that template-based attacks are ineffective and may even bac...
The findings highlight evaluation rubrics as a sensitive and manipulable control interface, revealing a system-level alignment risk that extends beyond evaluator reliability alone.
The TaCCS-DFA framework is designed, which combines online low-rank Fisher subspace estimation with an adaptive gating mechanism to enable efficient task-oriented fusion, and significantly tightens the upper bound on the output error.
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.
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