Security & Cryptography · Computer Science & AI
Cryptography & Security
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1,372 papers, from 4 September 2026 to 5 November 2026: 1,372 arXiv preprints.
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Newest papers, page 32
Temporal transformer CAN encoder with federated lightweight heads for anomaly detection
Modern vehicles rely on large numbers of Electronic Control Units (ECUs) that constantly exchange information over the Controller Area Network (CAN) bus.When Routing Reveals Membership: Privacy Leakage from MoE Router Telemetry
Mixture-of-Experts (MoE) language models produce routing information during inference that may be logged or exposed for monitoring, debugging, load analysis, and safety auditing.MRCert: Towards Post-deployment Patch Robustness Certification for Adversarially Patched Samples via Type-specific Masking
In post-deployment time, inputs to deep learning models may or may not be adversarially patched.When AI Finds Hidden Messages, Does It Report?
When an assistant encounters a message for another AI, does it tell its user?Safe at One Loop, Risky at Another: Aligning Safety Across Recurrent Depths in Looped Language Models
Looped Language Models (LoopLMs) provide a parameter efficient approach to scaling model capabilities through repeated use of shared parameters across recurrent steps.SoK: Failure Modes in Common Criteria Product Evaluation - A Taxonomy and Design-for-Evaluability Guidance
The Common Criteria (CC; ISO/IEC 15408) is the principal international framework for evaluating the security of IT products, and its certificates gate procurement across government, defense, and…Nullify: Null-Space Activation Steering for Training-Free LLM Unlearning
Large Language Models (LLMs) inevitably internalize substantial amounts of sensitive or private information during pre-training, while LLM unlearning aims to selectively erase specific knowledge to…Applying Security by Design at the Point of Execution: How Governed Security Requirements Affect the Security of AI-Generated Code
Security by design asks that security requirements are defined before code is written.DITTO: A Context-aware Pickle-based Pre-Trained Model Scanner for Effective Security Audits
Pre-trained models (PTMs) are widely distributed as serialized binaries, but their reuse often exposes software supply chains to deserialization attacks.BRANCH: Bypassing Multi-Scanner AI Guardrails
AI systems increasingly rely on Large Language Models (LLMs) as core reasoning engines, making them targets for prompt injection and jailbreaks.CPU-Auth: Device Fingerprinting for Authentication via DVFS Side-Channel
Lack of effective authentication has resulted in numerous security and privacy breaches, including unauthorized access to protected information, identity theft, and fraud.When Flaws Cascade: Understanding Vulnerabilities and Exploitation Chains in JavaScript Engines
JavaScript engines are pivotal to modern web browsers, enabling the execution of dynamic and interactive web applications.Power Side-Channel Membership Inference Attack on Embedded Machine Learning
Membership inference attacks (MIAs) threaten the privacy of machine learning (ML) training data by determining whether a sample was used to train a target model.Speedbumps: Rejection Attacks on Speculative Decoding
Speculative decoding is a popular technique for increasing the speed and reducing the costs of large language model (LLM) inference by verifying multiple draft tokens in a single target-model…CheckerBench: Can Long-Horizon Agents Synthesize Static-Analysis Checkers?
Static-analysis checker synthesis requires agents to interpret a defect specification, inspect a repository, implement analyzer-specific logic, and refine the checker through repeated compilation…CISB-Bench: An Auditable Source--IR Dataset of Compiler-Introduced Security Bugs
Compiler-introduced security bugs (CISBs) arise when an optimization, lowering, or instrumentation decision changes a security-relevant property of the generated program.HarnessSecurity-Bench: Do Security Mechanisms Really Protect Coding Agent Harnesses?
Coding agent harnesses mediate tool use and authorize actions, yet their security mechanisms and runtime effects remain incompletely characterized.SkillPoison: Progressive Skill Poisoning via Successful Experiences
Self-improving LLM agents increasingly distill successful experiences into persistent, reusable skills.Where Rules End and Judges Begin: Measuring the Judgment Boundary in Multi-Agent Systems Security
LLM-based multi-agent systems (MAS) engage tools, share memory, and delegate tasks, often encountering adversarial content.Adaptive Model Inversion Attacks Generalize a Privacy-Robustness Tradeoff
In this paper, we show that standard evaluations of high-resolution Model Inversion Attacks (MIAs) significantly underestimate training-data privacy leakage.