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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
Laptop Theft in a University Setting can be Avoided with ...
Azqa Nadeem, Marianne Junger · 2019-07-18 · via cs.CR updates on arXiv.org

Laptops have become an indispensable asset in today's digital age. They often contain highly sensitive information, such as credentials and confidential documents. As a result, the value of a laptop is an accumulation of the value of both the physical device itself and the cyber assets it contains, making it a lucrative target for theft. Educational institutions have a large population of potential victims of laptop theft. To mitigate this risk, we investigate whether a simple warning sign can reduce the opportunity for potential offenders. To this end, we have conducted an empirical study to observe the prevalence of students/staff leaving their laptops unattended at a university study hall at the Delft University of Technology in the Netherlands, both with and without a warning sign. We observed 148 out of 220 subjects leaving their laptops unattended in just three weeks. The results also showed that without the warning banner, 75.5% (83 out of 110) of subjects left their laptops unattended and with the warning, only 59.1% (65 out of 110) of subjects showed the same behavior, which is a significant reduction of 16.4%. In addition, a qualitative analysis was performed on the responses of subjects who left their laptops unattended after the warning banner was placed. The results showed a mix of convenience, and a blind trust on the safety of the faculty. In conclusion, a simple banner was effective in reducing the opportunity for laptop theft. However, the percentage of laptops left unattended was still high even after the introduction of the banner.