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AI_SAFETY

EU Regulatory Changes

1599 changes tracked across 24 compliance frameworks including DORA, NIS2, GDPR, EU AI Act, Cyber Resilience Act, and more.

All DORA NIS2 GDPR CSRD MaRisk ISO27001 EU_AI_ACT CRA DSA DMA eIDAS2 SOC2 PCI_DSS HIPAA ISO42001 AMLD6 PSD3 DATA_ACT GPSR CER EUDR CVE BREACH AI_SAFETY
arXiv: An IoT-Enabled Smart Home Automation System for Energy Efficiency with Web-Based Control
arXiv: Choose Wisely and Privately: Proactive Client Selection for Fair and Efficient Federated Learning
arXiv: Comparative Evaluation of Deep Learning Models for Fake Image Detection
arXiv: Ark: Offchain Transaction Batching in Bitcoin
arXiv: Privacy-Preserving Distributed Optimization Under Time Constraints Using Secure Multi-Party Computation and Ev...
arXiv: GenAI-Driven Threat Detection with Microsoft Security Copilot
arXiv: Precision and Privacy in Distributed Quantum Sensing: A Quantum Fisher Information Duality
arXiv: Rethinking Fraud Safety Evaluation: Multi-Round Attacks Reveal Safety-Utility Tradeoffs in Graph-Context LLM D...
arXiv: An Application-Layer Multi-Modal Covert-Channel Reference Monitor for LLM Agent Egress
arXiv: Heartbeat-Bound Hierarchical Credentials: Cryptographic Revocation for AI Agent Swarms
arXiv: Trusted Weights, Treacherous Optimizations? Optimization-Triggered Backdoor Attacks on LLMs
arXiv: Detecting Data Exfiltration through I2P Anonymity Networks: A Two-Phase Machine Learning Approach
arXiv: An exponential mechanism based on quadratic approximations for fine-tuning machine learning models with privac...
arXiv: SMA-DP: Spectral Memory-Aware Differential Privacy for Deep Learning
arXiv: Model Forensics in AI-Native Wireless Networks: Taxonomy, Applications, and Case Study
This publication introduces a taxonomy and framework for model forensics specifically designed for AI-native wireless networks, which are networks where artificial intelligence is deeply integrated...
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arXiv: MetaBackdoor: Exploiting Positional Encoding as a Backdoor Attack Surface in LLMs
This publication from May 2026 introduces a novel vulnerability in large language models, termed MetaBackdoor. The research demonstrates that an attacker can embed a hidden backdoor into an LLM by ...
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arXiv: Talk is (Not) Cheap: A Taxonomy and Benchmark Coverage Audit for LLM Attacks
This publication, a pre-print from arXiv dated May 14, 2026, introduces a new taxonomy and benchmark coverage audit for attacks on large language models (LLMs). It systematically categorises the ty...
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arXiv: Veritas: A Semantically Grounded Agentic Framework for Memory Corruption Vulnerability Detection in Binaries
This publication introduces Veritas, a novel AI-driven framework designed to automatically detect memory corruption vulnerabilities in compiled binary software. Unlike traditional static analysis t...
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arXiv: PickleFuzzer: A Case Study in Fuzzing for Discrepancies Between Python Pickle Implementations
This publication, titled PickleFuzzer: A Case Study in Fuzzing for Discrepancies Between Python Pickle Implementations, presents a new automated testing tool designed to find security and reliabili...
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arXiv: Analyzing Codes of Conduct for Online Safety in Video Games at Scale
This publication, a research paper from arXiv, does not represent a regulatory change but rather a significant analytical study that will inform future regulatory frameworks. The paper presents a l...
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