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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 Systematisation of Knowledge: Connecting European Digit...
Ben Biedermann, Matthew Scerri, Victoria Kozlova, Joshua Ellul · 2024-09-27 · via cs.CR updates on arXiv.org

The terms self-sovereign identity (SSI) and decentralised identity are often used interchangeably, which results in increasing ambiguity when solutions are being investigated and compared. This article aims to provide a clear distinction between the two concepts in relation to the revised Regulation as Regards establishing the European Digital Identity Framework (eIDAS 2.0) by providing a systematisation of knowledge of technological developments that led up to implementation of eIDAS 2.0. Applying an inductive exploratory approach, relevant literature was selected iteratively in waves over a nine months time frame and covers literature between 2005 and 2024. The review found that the decentralised identity sector emerged adjacent to the OpenID Connect (OIDC) paradigm of Open Authentication, whereas SSI denotes the sector's shift towards blockchain-based solutions. In this study, it is shown that the interchangeable use of SSI and decentralised identity coincides with novel protocols over OIDC. While the first part of this paper distinguishes OIDC from decentralised identity, the second part addresses the incompatibility between OIDC under eIDAS 2.0 and Web3. The paper closes by suggesting further research for establishing a digital identity bridge for connecting applications on public-permissionless ledgers with data originating from eIDAS 2.0 and being presented using OIDC.