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 56
Capable yet Parsimonious: Extracting and Characterizing Hidden Chain-of-Thought in Frontier Models
The rapid capability gains of frontier language models are widely attributed to improved reasoning abilities, yet this cannot be verified as raw CoT traces in closed-source systems are hidden.Decoding the Legalese: A Scalable and Quantitative Framework for Analyzing Corporate Privacy Policies
Even though privacy policies are the primary mechanism organizations use to disclose how they collect, process, and share personal data, they are difficult for average users to interpret, perhaps by…From Alignment to Access Control: A Framework for GenAI Policy Enforcement
Generative AI (GenAI) applications have flourished enabling users to chat with large language models, and to create agents to act on their behalf for a variety of tasks.Metrics Failure in LLM-Based Code Vulnerability Repair: An Empirical Study and a Change-Aware Screen
Large language models (LLMs) are increasingly applied to the automated repair of C/C++ security vulnerabilities, and compile rate is a commonly reported proxy for progress: whether the generated…A2M: Trace-Optimized Agent Hijacking in the MCP Ecosystem
Agents using the Model Context Protocol (MCP) rely on semantic matching to select tools from third-party servers, exposing a semantic supply-chain risk through attacker-controlled metadata and…Comparative Evaluation of Static Embedding Models for HTTP Request Anomaly Detection
Web applications are increasingly targeted by cyberattacks that exploit HTTP requests to evade security mechanisms.Ajar: Measuring Open Privilege in Agent Defenses
A language model agent acts through the tools it is given.Topological Signatures of Cyber-Attack Classes in Natural Visibility Graph Representations of Network Traffic
Natural Visibility Graph (NVG)-based representations provide a promising approach for capturing structural patterns in sequential network traffic.Improving Service Availability in KubeEdge-Based Architectures Using Lightweight Intrusion Detection
The increasing adoption of the Internet of Things (IoT) and cloud computing has accelerated the evolution of edge computing paradigms [1].Solidity Meets LLMs: A Transformer-Based Approach to Smart Contract Vulnerability Detection
The growing adoption of blockchain technologies, particularly the Ethereum platform, has amplified the critical role of smart contracts in decentralized applications.When Clients Are Orchestrated: Strategic Gradient Manipulation to Defeat Federated Learning Servers with Efficient Defense
Federated Learning enables decentralized model training by exchanging model updates--rather than raw data--with a central parameter server (PS).The Like Trap: Multi-Stage Poisoning against Agents in Similarity-based Recommendation 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.An Exposition of GPT Astra's Proof of Lower Bound on DP Continual Counting
The goal of this note is to give a detailed proof, to the best of our understanding, of the recent presentation by Harrison and Leeman (arXiv:2609.17650v01 and arXiv:2609.17650v02) of the proof by…MobileCybench: Evaluating Agent Vulnerability Discovery via Executable Probes
AI agents now report vulnerabilities faster than maintainers can review them.Structured Decomposition for Reliable LLM-Generated Access Control Policies
This paper presents an LLM-based system that translates natural-language access control policies (NLACPs) into executable Rego code for Open Policy Agent (OPA).From Bits to Beliefs: Recoverable Semantic Fingerprints for Black-Box Verification of Large Language Models
Open-weight large language models (LLMs) can be copied, modified, and redeployed behind black-box APIs, making post-release ownership verification difficult.Reinforcement Learning Inspired Black-box Adversarial Attacks for Computer Vision
Neural networks, both convolution or transformer based, are essential for modern computer vision systems.Temporal Generalization and Explanation Stability of Control Flow Graph Neural Networks for Malware Detection
Malware detection is a critical task in cybersecurity, and graph neural networks over control flow graphs have shown promising results for it.New lower bounds for CDS and $f$-routing
Understanding the entanglement cost of non-local quantum computation (NLQC) is relevant to complexity theory, cryptography, quantum gravity, and related areas.Dissecting Agentic Forensics: The Role of Triage, Prompting, and Evidence Arbitration in Open-World Fake Image Detection
Image forensics is increasingly an open-world problem: manipulations range from fully synthetic images to localized edits, splicing and swapping, while most forensic detectors remain specialized to…