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 26
Adversarial Robustness of Camera-Radar Sensor Fusion for Autonomous Driving
Autonomous driving (AD) relies on multi-sensor perception to interpret the surrounding environment.When Agents Talk, Secrets Travel: Topology-Driven Leakage and Recipient-Conditioned Sanitization in Multi-Agent LLM Systems
Multi-agent LLM systems (MALS) introduce a privacy-leakage problem that conventional sensitivity-based defenses miss, since information disclosed to one authorized agent can propagate through…ATTCK-R: Knowledge-Aware Long-Horizon Jailbreaking for Protected LLMs
As large language models are deployed behind increasingly sophisticated safety mechanisms, evaluating their robustness under realistic adversarial conditions becomes increasingly difficult and…Not All Challenges Are Equal: Evaluating Interactive Liveness Detection Against Real-Time Face Swaps
Remote identity verification assumes that a camera stream shows a live person, yet public real-time face-swap tools can replace that person before the stream reaches the verifier.CryptoFlowBench: Benchmarking Multi-Hop Reasoning on Blockchains for Cryptocurrency Fund Tracing
Pseudonymous accounts and complex smart-contract ecosystems substantially hinder the tracing of illicit cryptocurrency fund flows.Differential Privacy Protected Preference Alignment on Survey Derived Data
Preference alignment enables language models to better reflect human values, but the preference data contains sensitive information, especially when derived from surveys about political beliefs…PrivacyGuard: Source-Linked Sanitization and Locally Resolvable PII References for Cloud GUI Agents
Cloud graphical user interface (GUI) agents send instructions and screenshots to remote planners, exposing personally identifiable information (PII).Logit Leakage through Floating-Point Bias Addition
Language model APIs can expose token-specific biases while withholding logits and token probabilities.StableJudge: A Lightweight Adversarial Defense Framework for LLM-as-a-Judge
Large language models (LLMs) are increasingly used as judges to assign scalar scores that drive downstream decision-making, including tasks such as paper review and recommendation.Unsupervised Data Drift Monitoring for Deployed Deepfake Speech Detectors
Deepfake speech detectors are typically evaluated as binary classifiers on fixed benchmarks, but deployed systems face evolving attacks, codecs, speakers, and recording conditions, with labels…Beyond User-Side Defenses: Image Protection in Open-Weight Diffusion Models
Model providers can support image protection, but open-weight deployment introduces practical constraints.CWE-bench: Refocusing Agentic Security from Exploitation to Defense
Cybersecurity evaluations of AI agents have focused largely on offense, yet a working exploit does not show that an agent can make software safe.Can Rényi Accountants Beat Lossless Accountants for DP-SGD?
Recent frameworks in differential privacy (DP), such as privacy loss distributions and $f$-DP, provide lossless representations of the privacy leakage of mechanisms.Who is the 'I' in AI? Establishing Decentralized Identity and Accountability for Autonomous Agents
The rapid proliferation of autonomous AI agents in decentralized ecosystems challenges existing identity paradigms.Tight End-to-End Accounting for Differentially Private Synthetic Data
Differentially private (DP) pipelines often combine heterogeneous mechanisms, yet their guarantees are best analyzed using different notions of privacy (e.g., bounded range, zCDP, ADP).SSM-Attack: Learning Where to Perturb for Black-Box Face Privacy
Face recognition systems are deployed widely enough that a photograph shared online can be matched without its subject's consent.COMPASS: Membership Inference Attack Against Vision Large Language Models via Adaptive Noise Calibration
Vision large language models (VLLMs) are deployed in privacy-sensitive domains, raising training-data exposure concerns.VulnBump: A Benchmark for Fixing Vulnerable Dependencies in Real Projects While Keeping the Build and Tests Green
Software composition analysis (SCA) tools report far more vulnerable dependencies than teams fix: in Snyk Open Source production data, 94% of vulnerability findings have a known fixed version, yet…Mitigating Black-Box Score-Based Query Attacks via Gradient Confusion
Score-based black-box adversarial attacks pose a serious threat to deployed machine learning systems by exploiting repeated model queries to craft adversarial examples, requiring neither access to…Fast Forgiving Base64 Decoding with SIMD Instructions
On the Internet, we use the Base64 format to represent binary data (e.g., images or cryptographic keys) as text.