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.
Get the few papers worth your time in Cryptography & Security every morning.
Follow Cryptography & Security and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 11
A Certified Robustness Framework for Backdoor Poisoning Attacks using $f$-Divergences
Machine learning systems trained on untrusted data are vulnerable to data and backdoor poisoning attacks, in which an adversary corrupts training and test samples to manipulate predictions at…Intellectual Property Protection of Hyperdimensional Computing Classifiers: Black-Box Ownership Verification via Model Watermarking
Hyperdimensional computing (HDC) offers efficient learning and inference for resource-constrained systems, yet ownership verification of its models remains underexplored.The Target Agent Is Its Own Best Critic but a Poor Proposer: Self-Improved Red Teaming
Automatic red teaming increasingly relies on large language models (LLMs) to iteratively diagnose failed attacks and propose improved adversarial prompts or injections.CoSA: The Conflict of Skills Attack in Real-World LLM Agent Ecosystems
Agent Skills allow LLM agents to combine reusable capabilities, but checking each Skill in isolation cannot rule out policy violations when they are composed.SoK: Timestamps Are Not a Time Model: Rethinking Temporal Reasoning in Host-Based Intrusion Detection
Host-based intrusion detectors order events, window audit streams and sequence attack stages by their timestamps.Trustworthy Recursive Self-Improvement in the Era of Large Models: Foundation, Risks, Evaluation and Open Challenges
AI systems built around large models increasingly use experience and feedback to make persistent changes to models, prompts, memories, tools, and workflows.Then there is prompt injection, a malicious email, ...: The Wild Wide West of OpenClaw Agentic System Security
AI-powered personal assistant frameworks such as OpenClaw combine LLM reasoning, persistent memory, tool invocation, local execution, and web-based workflows.JANUS: Synthesizing Cross-Layer Defenses Against Web Deserialization Attacks
Unsafe deserialization turns untrusted data into attacker-controlled execution, and a single vulnerability can admit diverse exploit variants that evade defenses tailored to a known exploit.The Agent in the Middle: How AI-Mediated Access Reshapes Web Vulnerability Exploitation
Web services increasingly expose backend interfaces that let users delegate tasks to AI agents, which invoke service operations directly without navigating websites.Adversary Brains: Hypothesis-Based Logical Signatures for Threat Actor Detection with LLMs
An adversary brain is an LLM-based model of a threat actor's behavior, held as an evolving logical signature: a hypothesis with enough structure that data can test it continuously, without a person…Cheap AI-Assisted Reverse Engineering and What It Will Do
Generative AI is putting the law of reverse engineering (RE) under severe strain.A Category-Selective Encryption Framework for Privacy Protection of UAV Images
Imagery captured by unmanned aerial vehicle (UAV) systems increasingly raises privacy concerns, as UAV aerial surveillance routinely captures sensitive objects such as pedestrians and vehicles…Atomic Security Concerns: Towards a Foundational Language for Security Knowledge Representation
Cybersecurity governance, risk management, compliance, and security architecture rely on numerous concepts, including security properties, domains, controls, risks, implementation measures…Reva: Real-Time Vulnerability Detection through Contextual Probing of Large Language Models
A vulnerability costs more to fix the later it is discovered.Information-Theoretic Secure Aggregation With Heterogeneous Client Quantization
In federated learning (FL), secure aggregation enables a server to compute the sum of local model updates of $N$ clients, without revealing any information on the individual model updates to the…I-HITL: Inalienable Human-in-the-Loop
Human oversight is a pillar of AI safety.Pricing Cross-Bank Context in Federated Anti-Money Laundering
Most graph-based Anti-Money Laundering (AML) methods assume access to a pooled transaction graph containing all accounts and payments, which in reality does not exist.Log-To-Leak: Prompt Injection Attacks on Tool-Using LLM Agents via the Model Context Protocol
LLM agents increasingly access external tools through the Model Context Protocol (MCP), but the natural-language metadata used to describe those tools creates a prompt-injection surface.Bringing Hardware Security Education to All: A Seamless Curriculum Integration Approach
Cybersecurity education has predominantly focused on software and network security, under the assumption that the underlying hardware is trustworthy.Privately Clipping Heavy-Tailed Data
Summing vectors is a basic task in differentially private data analysis.