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 52
AGATE: Provenance-Based Runtime Defense Against Compositional Attacks on LLM Agents
LLM agents can produce harmful effects through sequences of ordinary operations.FeatMark: Feature-level Watermark Protection against Mimicry Attacks with Diffusion Models
Text-to-image diffusion models enable data-efficient "mimicry" attacks, wherein adversaries fine-tune the model on a handful of public photos to synthesize convincing forgeries of a target individual.FARE: Forensic Acceptance Region Estimation for Catching Bait-and-Switch Image Generators
Modern AI image generators are increasingly deployed as opaque APIs, where customers can query the deployed service, but cannot inspect model weights or architecture.Can Pixels Alone Reveal Image Origin? Minimax Limits and Learnable Interfaces for Passive Provenance
Passive image provenance asks whether pixels alone can reveal where an image came from: a human, an aggregate AI class, or a particular generator.TempQ-Jail: Query-Constrained Candidate Ranking for Text-to-Video Jailbreak Attacks
Existing text-to-video (T2V) jailbreak methods mainly seek more effective or stealthier attack candidates.MetaPermit: Scalable and Auditable Access Control for AI Agents via LLM-Inferred Meta-Attributes
The rise of autonomous AI agents equipped with tools has introduced significant security risks, ranging from unintended tool misuse to adversarial manipulation through Indirect Prompt Injection…AuthGuard-R: Safety-Compliant Mission Hijacking and Dual-Gate Defense for LLM-Controlled Robots
Large language models are increasingly used as high-level planners for mobile robots, robot manipulators, and autonomous vehicles.JevAdvBench: A Benchmark and Black-Box Attacks for Reinforcement Learning for Calibrated Decisions Models
Models trained with reinforcement learning for calibrated decisions (RLCD), such as Jev, answer a typed question about an input, the state, with a probability, a choice, or a score, and software…HyperErase: Scale-Calibrated Hypernetwork for Multi-Concept Erasure in Text-to-Image Models
Recent advances in text-to-image (T2I) generation have substantially improved visual synthesis, but have also raised increasing safety concerns due to their potential to generate harmful or…Geometric Inconsistency Localization in Multi-View Image Sets
Novel view synthesis (NVS) models can produce realistic new views of the same scene from different viewpoints.The planted tensor problem over finite fields: algorithms and cryptography
Inspired by the planted clique problem for random graphs, we introduce the planted totally-isotropic space problem for random tensors as follows.Resource-Optimized and Energy-Aware Agentic AI Framework Anchored on Blockchain for Secure Software Supply Chains
This paper proposes a blockchain-backed agentic security framework designed to safeguard the complete software development lifecycle (SDLC) while also securing the agentic AI components responsible…AgentXploit: Autonomous Repository-to-Runtime Red-Teaming for AI Agents
AI agents combine language models with external data and tools that can modify files, call APIs, or execute code.Towards Understanding LLM-Based Log Anomaly Detection: An Empirical Study of Performance, Efficiency, and Robustness
Large language models (LLMs) have demonstrated promising performance in log anomaly detection, yet how their adaptation strategies, architectures, and deployment configurations affect detection…How Much Must a Private Mempool Hide? Exact Leakage Thresholds for Sandwich Attacks
Private and encrypted mempools hide pending transactions to stop sandwich attacks and other forms of maximal extractable value (MEV), but what they hide is rarely everything: a transaction's pair…Context-Aware Functional Modeling for Android Third-Party Library Detection
Third-party libraries (TPLs) are widely used in Android apps, but their reuse can introduce security risks and interfere with downstream program analyses.Verifiable Randomness for Blockchain-Based Lottery Systems
As lotteries and other high-stakes decentralized applications increasingly depend on unpredictable randomness for their operations, the lack of a secure and transparent on-chain random number…Region-Level Black-Box Defense Against Stealthy Embedding-Space Backdoors in CLIP
Contrastive Language--Image Pretraining (CLIP) has emerged as a dominant vision backbone due to its strong transferability and zero-shot capabilities.From Source Code to Network Profile: Automated and Traceable MUD Profile Generation for IoT Devices
The Manufacturer Usage Description (MUD) standard allows IoT manufacturers to define expected network behaviors in a MUD file.A Large-Scale Benchmark and Risk Assessment of Traffic Analysis Attacks on Cloud LLM Services
Cloud-based Large language model (LLM) services create a network-level traffic side channel that can expose model, prompt, and task behavior despite encryption.