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 58
SelfOp: An Optimization Algorithm for Self-Improving Security Agents
LLM agents are increasingly used for security tasks: vulnerability discovery, exploit reproduction, and patch generation.The Price of Safety: Benign-Case Utility and Token Overhead of Memory-Poisoning Defenses in LLM Agents
Memory-poisoning defenses for LLM agents are typically evaluated by their ability to prevent attacks.Beyond Single-Model Injection: A Threat Model and Defense Architecture for Prompt Injection in Multi-Agent Systems
Existing prompt injection research focuses on single-model chatbot scenarios, where an attacker manipulates one LLM through crafted input.When Agentic Trust Crosses Organizational Boundaries: Structural Externalization and a Reference Model for Trust Evidence
Agentic systems increasingly invoke tools, services, data, and other agents across organizational boundaries, yet a relying party cannot assess a delegated action solely from producing-domain…Dual-Locking Learned AI Models: A PIN-Based Sparse QIM Watermarking and Adaptive Index Permutation Approach
We present a dual-locking method for securing trained neural networks that combines key-driven index permutation with PIN-based watermarking based on Sparse Quantization Index Modulation (QIM).An LLM-Assisted AutoML Framework for Intrusion Detection in IoT Networks
Internet of Things (IoT) systems are increasingly deployed in smart homes, transportation, energy systems, and critical infrastructure.LLMs as Linguistic Chameleons: Decoupling Semantics and Structure for Privacy-Preserving Communication
As Large Language Model (LLM) APIs become increasingly integrated into privacy-sensitive workflows, ensuring inference-time privacy without compromising task utility remains a major challenge.SoK: From Finding to Deployment: Systematizing the OS Kernel Bug Lifecycle
Automated kernel bug discovery has advanced rapidly.Security of Agent-Integrated Software: When Human Operations and Agent Actions Coexist
Agent-Integrated Software (AIS) embeds an intelligent agent in a conventional application, supporting both human operations and agent actions.Authorization Revocation for Long-Running AI Agents: Root-Scoped Quiescence under Delegation and Asynchronous Execution
Long-running AI agents outlive initiating processes through credentials, delegated tasks, queues, callbacks, reservations, and provider-side operations.Identifying Security Platform Product Abuse with Machine Learning
Product abuse is an individually rare, but growing, problem across the SaaS industry.Conformal Privacy Auditing: Calibrated Re-identification Attacks with Statistical Guarantees
Empirical identity leakage from released text is increasingly driven by attackers that combine large language models (LLMs) with auxiliary knowledge to link documents to individuals.CESBench: Benchmarking Large Language Models on Cryptographic Engineering Security for IoT Devices
For Internet of Things (IoT) devices, a secure algorithm alone is not enough: an attacker with physical access can attack the implementation directly, and its flaws are hard to fix once deployed.HE-Guardrail: A Homomorphic Guardrail Against Jailbreak Attacks for Encrypted Large Language Model Inference
Homomorphic encryption (HE) has emerged as a promising approach to privacy-preserving machine learning (PPML), enabling computation directly over encrypted data.ServeGuard: Verifiable, Bounded-Residual Confinement of Operator-Invisible Channels Without Revealing the Certified Read Factor
Third-party adapters for open-weight language models ship as opaque weight matrices; a recipient cannot check whether an adapter hides a backdoor without trusting the publisher or inspecting the…Micro-Collaborative Poisoning: A Distributed Attack on RAG Systems
Retrieval-Augmented Generation (RAG) improves large language models by grounding outputs in external knowledge sources, but this dependency also creates a surface for poisoning attacks.CIPL: A Channel-Aware Framework for Recoverable Privacy Leakage in LLM Agents
Privacy leakage in LLM agents is commonly evaluated within individual components such as memory, retrieval, or tool-use pipelines, which makes it difficult to distinguish internal exposure from…TERMon: Detecting Persistent Behavioral Threats in Edge AI via Hardware-Native Ternary Runtime Monitor
Edge AI accelerators are increasingly deployed in safety-critical environments, where model outputs may control physical actuators, make access-control decisions, or trigger alarms.CASCADE Against Jailbreaks: Combination Across Stages with Controlled Attack-Defense Evaluation
Defenses against jailbreak attacks on Large Language Models (LLMs) operate at different pipeline stages, such as input modification or output guard, but it remains unclear which defenses to deploy…Watermarkable Multi-Draft Speculative Sampling via Poisson Processes
Large language models (LLMs) have achieved state-of-the-art performance across a wide range of tasks, motivating two important aspects of deployment: inference efficiency and output provenance…