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 36
From Sandbox to Enforcement: Confidence-Qualified Threat Intelligence for Critical Infrastructure
Security operations centres and national incident-response teams defending critical infrastructure collect abundant threat data yet struggle to turn it into actionable intelligence.ATLAS-AL: Adaptive Trust-Region for Latent Adversarial Searches via Active Learning
Security evaluation of learning-based systems requires more than just testing the system against a fixed collection of attacks.Weight Oracles: Reading Neural Network Weights with Language Models
Interpretability methods for neural networks are predominantly reactive: they analyse activations produced during specific forward passes, requiring known inputs to find hidden capabilities such as…Evaluating Behavioral Context for Interpretable IAM Policy Risk Scoring in Cloud Environments
IAM policy analysis typically emphasizes the authorization capabilities encoded in a policy, but security analyst review priority may also depend on the behavioral and environmental context…Can Power Draw Constrain Covert Compute? Limits of Analogue Verification for AI Governance
Frontier AI treaties or agreements on limiting computation require external verification; an external auditor must be able to confirm how much computation actually ran and that parties are adhering…Deep Defence on Wheels: A Dual Intrusion Detection System Architecture for Comprehensive In-Vehicle Network Security
Increasing connectivity to the outside world and the lack of inbuilt security mechanisms have made legacy intra-vehicular networks vulnerable to cyberattacks.Harmful SFT Leaves a Continuous Trace in LLM Checkpoint Updates
Safety auditing of post-trained large language models typically relies on model behavior, requiring model execution and depending on the coverage of available evaluations.Not What a Child Expressed: Auditing the Sign-to-Text Safety Interface in Child-Facing AI
Automatic sign language translation (SLT) has entered consumer products, turning American Sign Language into English text for dictation, messaging, and queries put to a conversational assistant.Safeguarding LLMs via Model-Agnostic Latent Safety Signals from Dark Knowledge
LLMs have advanced rapidly, raising growing concerns about their safety.Adversarial RL for Port-Scan Evasion: Attacker Feature Visibility in Edge-Deployed IDS
Machine learning-based intrusion detection systems (IDS) are increasingly used in resource-constrained Internet of Things (IoT) environments, yet their robustness is often evaluated against static…Invisible Ink, Visible Lies: How Production Watermarking Causes LLMs to Hallucinate
Text watermarking helps identify AI-generated content, but its effect on factual reliability remains underexplored.Bounded Reasoning: Cognitive Hierarchy in Human-versus-AI Cyber Defense
Human-agent evaluations often compress interaction into a single performance score, even when human and automated policies adapt differently over time.WLPA: A Network Management Framework for Allocating Scarce Quantum-Safe Link Postures under Weakest-Link Exposure
Network operators migrating distributed systems to post-quantum and quantum-safe cryptography face a resource-management problem: quantum key distribution (QKD) gives the strongest guarantee…Static Bootstrap Placement for Encrypted Language Model Decoding
Language models increasingly serve prompts that carry private data, and secure inference under homomorphic encryption lets a client outsource the computation without revealing the prompt.Runtime Authorization of Self-Generated Subgoals in Long-Horizon Tool-Using AI Agents
Long-horizon tool-using AI agents create subgoals, replan, delegate work, and compose sibling results.Hidden Risks of Jev: An Empirical Study of Security, Privacy, and Dual Use
Jev turns natural-language questions into typed answers and probabilities with low latency and cost, enabling applications to route requests and select tools.Characterizing Security Effects of OSS Vulnerabilities in Agent Systems
Software agents increasingly depend on open-source components when executing tools and interacting with external systems.Private Component-by-Component Learning
We study differentially private learning problems in the realizable setting, where a hypothesis is specified by $k$ components.VulValidate: Auditing Function-Level Vulnerability Labels with Executable Evidence
Reliable learning-based vulnerability detection requires high-quality labels, yet datasets built from vulnerability-fixing commits may label functions as vulnerable simply because they were changed…Blocking at the Boundary: Auditing Long-Horizon Agents against Staged Prompt Injection
Long-horizon agents consume external content, invoke tools, and modify persistent state.