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AI_SAFETY

EU Regulatory Changes

1550 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: Memory Provenance Laundering in LLM Agents: A Non-Amplification Firewall for Persistent Memory
arXiv: StraightDP: Geometry-Aware Differential Privacy for Rectified-Flow Transformers
arXiv: GoldenRetriever: Non-Interactive Homomorphic Encrypted Retrieval for Privacy-Preserving RAG
arXiv: Mind the Gap: Policy vs Reality in Post-Quantum TLS Deployment
arXiv: MESS: Fast and Private Semantic Search on Multi-Graph HNSW
arXiv: A Biometric Sensor Network to Enable Real-Time Measurement of Individual Student Engagement in STEM Lecture En...
arXiv: Hollow-LLM Attack: Computationally Trivial Weights in Zero-Knowledge Verification of LLM Inference
arXiv: YazSes: An Offline, Privacy-First, Cross-Platform Hold-to-Talk Voice-Dictation System
arXiv: TextCloak: Thwarting Unauthorized LLM Exploitation via RL-Driven Unlearnable Text
arXiv: Partial Derandomization for Leakage-Resilient Shamir's Secret Sharing over Composite Order Fields
arXiv: Blockchain Transaction Simulation Phishing
arXiv: Formalization of security
The publication, titled "Formalization of security" under the AI_SAFETY framework, introduces a rigorous mathematical and logical structure for defining and verifying security properties in AI syst...
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arXiv: Implementing Homomorphic Encryption-Based Logic Locking in System-on-Chip Designs
A new academic paper proposes using homomorphic encryption to implement logic locking in system-on-chip designs, a technique that could allow hardware to be securely activated or deactivated post-m...
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arXiv: Cybersecurity Detection Classification with Reasoning-enabled Language Models
A new research paper, published on arXiv on July 30, 2026, introduces a method for improving cybersecurity threat detection using large language models with advanced reasoning capabilities. The stu...
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arXiv: Emerging Challenges in Threat Modeling for GenAI-Augmented Systems: A View from the Trenches
This publication is a research paper from arXiv, not a binding regulatory change, but it offers critical guidance for compliance teams navigating the emerging field of generative AI. The paper exam...
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arXiv: Encryption-Compatible Clustered Federated Learning via Distributed Expectation-Maximization over Metadata
The publication introduces a new technical framework, Encryption-Compatible Clustered Federated Learning via Distributed Expectation-Maximization over Metadata. This is a research paper, not a regu...
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arXiv: Demystifying DRAM Read Disturbance: Bridging the Gap Between Experimental Characterization and Device-Level Mo...
This publication is a technical research paper, not a regulatory change, but it has significant compliance implications for hardware security. The paper presents a new framework for understanding a...
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arXiv: Security of World-Model-Based Embodied AI: A Lifecycle of Threats, Defenses, and Evaluation
A new academic paper, published on arXiv, provides a comprehensive lifecycle analysis of security threats and defenses for world-model-based embodied AI systems. This is not a new regulation, but a...
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arXiv: Secure Aggregation for Privacy-Preserving Federated Learning on Clinical EEG Data
A new research paper proposes a technical framework for applying secure aggregation to federated learning models trained on clinical electroencephalogram (EEG) data. Federated learning allows multi...
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arXiv: Technology-Enhanced Tabletop Exercises for Cybersecurity Education: Lessons Learned
A new research paper, published on arXiv, explores the use of technology-enhanced tabletop exercises for cybersecurity education, with direct implications for AI safety compliance. The study presen...
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