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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
Advancements in Biometric Technology with Artificial Inte...
Konark Modi, Lakshmipathi Devaraj · 2022-12-16 · via cs.CR updates on arXiv.org

Authentication plays a significant part in dealing with security in public and private sectors such as healthcare systems, banking system, transportation system and law and security. Biometric technology has grown quickly recently, especially in the areas of artificial intelligence and identity. Formerly, authentication process has depended on security measures like passcodes, identity fobs, and fingerprints. On the other hand, as just a consequence of these precautions, theft has increased in frequency. In response, biometric security was created, in which the identification of a person is based on features derived from the physiological and behavioral traits of a human body using biometric system. Biometric technology gadgets are available to the public as they are embedded on computer systems, electronic devices, mobile phones, and other consumer electronics. As the fraudulent is increasing demand and use of biometric electronic devices has increased. As a consequence, it may be possible to confirm a person's distinct identification. The goal of this study is to examine developments in biometric systems in the disciplines of medicine and engineering. The study will present the perspectives and different points of view of the secondary data, highlighting the need for more in-depth understanding and application of biometric technology to promote its development in the digital era. The study's findings may inspire people and businesses to more effectively incorporate biometric technologies in order to reduce the risks to data and identity security.