Security & Cryptography · Computer Science & AI
Cryptography & Security
The newest papers in Cryptography & Security that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
1,372 papers, from 4 September 2026 to 5 November 2026: 1,372 arXiv preprints.
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Newest papers, page 33
The Model Plants the Trigger: Answer-Side Backdoor Attacks in Multi-Turn Large Language Models
Safety alignment in Large Language Models (LLMs) remains vulnerable to backdoor attacks.When Can Stateless Recovery Defeat Byzantine Quorum Safety? A Tight Normal Form for Single-Step BFT
Byzantine quorum safety relies on correct replicas refusing to sign conflicting values.The Amplifier Effect: Human-Factor Risks of AI-Suggested Correlation and Auto-Propagation in Multi-Framework GRC Self-Assessment
Multi-framework Governance, Risk and Compliance (GRC) platforms increasingly automate the link between an organisation's self-assessment answer and the compliance obligations that answer is said to…Preparing an AI-Augmented SIEM for the EU Cyber Resilience Act: A Practitioner Case Study
The EU Cyber Resilience Act (CRA), Regulation (EU) 2024/2847, makes product cybersecurity a lifecycle obligation for products with digital elements on the EU market: risk assessment, vulnerability…Explainable Rule Mining of IPv6 Extension-Header Presence Patterns from Paired-Vantage Captures
IPv6 extension headers (EHs), such as fragmentation, segment routing, and in-situ telemetry, are operationally important yetwidely dropped in transit, and characterising their behaviour from packet…When Tools Lie: Reliability of Mathematical Agents Under Corrupted Tool Feedback
Mathematical problem solving often requires deterministic computational steps that agents delegate to tools and implicitly trust.Surviving the Router: Optimizing Skill Injections for Retrieval and Execution
AI agents increasingly rely on modular third-party "skills" that are dynamically selected by skill routers to execute complex tasks.Rethinking Visual Provenance: Detection and Watermarking Across Direct Visual Generation and LLM-Driven Code Rendering
AI systems create images and videos with image/video generation models or by writing code and graphics descriptions that are then rendered.On the Intrinsic Limited Robustness of Latent-Based Watermarking
Existing latent-based watermarking methods for diffusion models have overestimated their robustness to image distortions, including geometric transformations such as rotation, scaling, and…Newer and Bigger, but Safer? A Longitudinal Study of the Functionality-Security Gap in LLM-Generated Code
Large Language Models (LLMs) are widely used to generate code.HE-OFT: Privacy-Preserving One-Shot Federated Fine-Tuning under Homomorphic Encryption
Many organizations adapt large pretrained models to their own tasks by fine-tuning on private data.MARCO: The Radioactive Watermark for Protein Generative Models
Protein Generative Models (PGMs) have revolutionized structural biology by enabling the design of complex 3D protein structures from sequence data.Learning from Failures: A Failure-Driven Prompt Refinement for LLM-Based Vulnerability Analysis
Large Language Models have emerged as promising tools for software vulnerability analysis, but their effectiveness depends heavily on prompt design.Decoy and disclosure radii of invariant shape descriptors
A recognizer that compares rotation-invariant descriptors sees a surface only up to the fiber of the descriptor.Ariadne's Thread of LipSync: Unraveling Forgeries via Inconsistency between Lip Motions and Head Poses
Recent advances in LipSync generation technology have led to the creation of highly realistic videos, posing severe societal risks.One-Shot Private Confidence Regions via Resampling
We propose a simple framework for constructing differentially private confidence regions \textit{in one shot}, i.e., by adding noise only to the final resampling quantile instead of privatizing the…Federated Bayesian Surveillance of Mechanical Thrombectomy Adverse Events: A Population Risk Layer for Surgical Digital Twins
Learned surgical simulators and world models can roll out plausible procedural futures, but they carry no grounded estimate of how often interventional devices actually harm patients.RAG-PIBench: A Leakage-Aware Benchmark for Prompt-Injection Detection in Trustworthy RAG Systems
Retrieval-Augmented Generation (RAG) systems are vulnerable to prompt-injection attacks embedded in retrieved content.Semantic Behavioral Watermarking: Paraphrase-Robust and Forgery-Resistant Provenance for LLM Agents
Behavioral watermarking embeds an owner identifier in an LLM agent's high-level action choices, giving provenance without touching output tokens.Secure Speculative Decoding for Large Language Models
Speculative decoding accelerates inference for a large language model (LLM), referred to as the \emph{target model}, by first using a smaller model, referred to as the \emph{draft model}, to…