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 16
CertMoE: Robustness Certification for Mixture-of-Experts LLMs via Routing-Aware Smoothing
Provable robustness is a cornerstone of trustworthy machine learning, aiming to guarantee model predictions under adversarial perturbations.VX-One: Typed, Calibrated Decision Heads for Real-Time Perimeter Triage
Perimeter triage faces a latency/semantics trade-off: signature engines are fast and format-safe but blind to unseen attacks, while generative models are semantic but slow and unparseable.Protection Is Not One Event: A Survey of RAG Protection Research by Measured Endpoint
Yet RAG protection studies use incompatible evaluation metrics, datasets, and threat models.MPIDetector: Detecting Multi-modal Prompt Injection via LLM-based Reasoning
With the rapid integration of Multi-modal Large Language Models (MLLMs) into real-world applications, Prompt Injection (PI) has emerged as a critical security threat.JANUS: Agentic Cross-Language Fuzzing Harness Generation for Android Native Libraries
Modern Android apps extensively rely on native libraries, bridging Java/Kotlin and C/C++ through the Java Native Interface (JNI).Automated screening of privacy risks in medical AI
Medical artificial intelligence (AI) models are often shared without their training data, assuming this protects the patients who contributed them.On the Adversarial Vulnerability of Neural Receivers with Unrolled LDPC Decoders
Neural receivers for 5G New Radio (NR) match classical model-based receivers in link-level performance, but their robustness to adversarial perturbations at the receiver input remains underexplored.Data-Void Exploits in Web-Searching LLMs
Web-searching Large Language Models (LLMs) have changed how users seek online information: instead of sifting through ranked lists of links, users read synthesized answers.Agent Mosaic: Recognizing Confidentiality Leaks in Agentic LLM Systems
Modern LLM agents can retrieve information from accessible documents, and then disclose a sensitive conclusion assembled from them.Beyond End-to-End Recovery: Towards a Better Understanding of LLM Steganography via Rolewise Decomposition
In large language model (LLM) steganography, an encoder hides a private message in an otherwise ordinary response, as text transmitted to a decoder, who attempts to recover it.Privacy-Preserving Personalized Federated Learning (PPP-FL) for Medical Imaging
Federated learning (FL) is a distributed machine learning paradigm that reduces transmission costs, mitigates cross-border data sharing restrictions, and enhances privacy by keeping raw data on…Beyond the Prompt: Recovering Hidden Concepts in Text-to-Image Models
Text-to-image models can generate visual concepts that their prompts never mention, and recent work shows that such associations can be implanted so that ordinary prompts trigger them.Adversarial Benchmarks and BenchDoor Attacks: Exploiting Benchmark Incentives for Backdoor Attacks
Machine learning benchmarks act as guideposts for model development and spur the creation of training datasets intended to improve benchmark scores.Act on Your Behalf, Beyond Your Authorization: Benchmarking LLM Agent Authorization Alignment
When an LLM agent acts on behalf of a user, it is expected to act within the authorization scope the user grants.The Show-Up Attack: When Subagents Win Over Their Supervisor
Multi-agent systems are increasingly deployed to coordinate multiple large language model (LLM) agents.Local Allow, Global Deny: Why Per-Action Authorization Does Not Compose in LLM Agents
Autonomous LLM agents act through tools under per-action authorization: a local guard screens each tool call in isolation.A Unified Attack Framework against Statistical Generative Watermarks for Large Language Models
Watermarking has emerged as a key tool for identifying text generated by large language models (LLMs), with current schemes embedding statistical signals into the generation process to enable later…CAESAR: Mixed Reality Search-and-Rescue Platform for Cognitive Attack Evaluation
Mixed Reality (MR) enables immersive training by tightly coupling virtual content with the physical environment and supporting embodied interaction.CyberHull: Deterministic Malicious URL Isolation via Convex Hull
The emergence of increasingly sophisticated and evasion-resistant phishing attack strategies represents a significant threat to modern cybersecurity, particularly in cyber-physical systems and…Privacy Accounting for Empirical Denoisers
Diffusion models have emerged as the foundation of modern generative systems, yet their high memorization capacity raises privacy concerns.