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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
A Comparative Risk Analysis on CyberShip System with STPA...
Rishikesh Sahay, D. A. Sepulveda Estay, Weizhi Meng, Christian D · 2022-12-21 · via cs.CR updates on arXiv.org

The widespread use of software-intensive cyber systems in critical infrastructures such as ships (CyberShips) has brought huge benefits, yet it has also opened new avenues for cyber attacks to potentially disrupt operations. Cyber risk assessment plays a vital role in identifying cyber threats and vulnerabilities that can be exploited to compromise cyber systems. A number of methodologies have been proposed to carry out these analyses. This paper evaluates and compares the application of three risk assessment methodologies: system theoretic process analysis (STPA-Sec), STRIDE and CORAS for identifying threats and vulnerabilities in a CyberShip system. We specifically selected these three methodologies because they identify threats not only at the component level, but also threats or hazards caused due to the interaction between components, resulting in sets of threats identified with each methodology and relevant differences. Moreover, STPA-Sec which is a variant of the STPA is widely used for safety and security analysis of cyber physical systems (CPS); CORAS offers a framework to perform cyber risk assessment in a top-down approach that aligns with STPA-Sec; and STRIDE (Spoofing, Tampering, Repudiation, Information disclosure, Denial of Service, Elevation of Privilege) considers threat at the component level as well as during the interaction that is similar to STPA-Sec. As a result of this analysis, this paper highlights the pros and cons of these methodologies, illustrates areas of special applicability, and suggests that their complementary use as threats identified through STRIDE can be used as an input to CORAS and STPA-Sec to make these methods more structured.