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cs.CR updates on arXiv.org

Agentic Vulnerability Reasoning on Windows COM Binaries From Beats to Breaches:How Offensive AI Infers Sensitive User Information from Playlists Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems Token-Efficient Change Detection in LLM APIs Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verification Trident: Improving Malware Detection with LLMs and Behavioral Features When Alignment Isn't Enough: Response-Path Attacks on LLM Agents RefusalGuard: Geometry-Preserving Fine-Tuning for Safety in LLMs Checkerboard: A Simple, Effective, Efficient and Learning-free Clean Label Backdoor Attack with Low Poisoning Budget Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking Secret Stealing Attacks on Local LLM Fine-Tuning through Supply-Chain Model Code Backdoors Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents Defusing the Trigger: Plug-and-Play Defense for Backdoored LLMs via Tail-Risk Intrinsic Geometric Smoothing Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards Behavioral Canaries: Auditing Private Retrieved Context Usage in RL Fine-Tuning FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models Text Steganography with Dynamic Codebook and Multimodal Large Language Model An AI Agent Execution Environment to Safeguard User Data TwoHamsters: Benchmarking Multi-Concept Compositional Unsafety in Text-to-Image Models Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility Hardening x402: PII-Safe Agentic Payments via Pre-Execution Metadata Filtering QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits Hijacking Text Heritage: Hiding the Human Signature through Homoglyphic Substitution Like a Hammer, It Can Build, It Can Break: Large Language Model Uses, Perceptions, and Adoption in Cybersecurity Operations on Reddit Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation One Word at a Time: Incremental Completion Decomposition Breaks LLM Safety Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review
Efficiency Improvements for Encrypt-to-Self
Jeroen Pijnenburg, Bertram Poettering · 2020-09-06 · via cs.CR updates on arXiv.org

Recent work by Pijnenburg and Poettering (ESORICS'20) explores the novel cryptographic Encrypt-to-Self primitive that is dedicated to use cases of symmetric encryption where encryptor and decryptor coincide. The primitive is envisioned to be useful whenever a memory-bounded computing device is required to encrypt some data with the aim of temporarily depositing it on an untrusted storage device. While the new primitive protects the confidentiality of payloads as much as classic authenticated encryption primitives would do, it provides considerably better authenticity guarantees: Specifically, while classic solutions would completely fail in a context involving user corruptions, if an encrypt-to-self scheme is used to protect the data, all ciphertexts and messages fully remain unforgeable. To instantiate their encrypt-to-self primitive, Pijnenburg et al propose a mode of operation of the compression function of a hash function, with a carefully designed encoding function playing the central role in the serialization of the processed message and associated data. In the present work we revisit the design of this encoding function. Without questioning its adequacy for securely accomplishing the encrypt-to-self job, we improve on it from a technical/implementational perspective by proposing modifications that alleviate certain conditions that would inevitably require implementations to disrespect memory alignment restrictions imposed by the word-wise operation of modern CPUs, ultimately leading to performance penalties. Our main contributions are thus to propose an improved encoding function, to explain why it offers better performance, and to prove that it provides as much security as its predecessor. We finally report on our open-source implementation of the encrypt-to-self primitive based on the new encoding function.