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◬ AI & Machine Learning Aug 04, 2026
A Decade of Healthcare Cyber Threats: Empirical Analysis, Evidence-Based Prioritisation, and AI Threat Model

arXiv:2608.00901v1 Announce Type: new Abstract: Healthcare systems face persistent and evolving cyber threats, yet how adversarial tactics and techniques have shifted over time has not been systematic…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Multi-LLM Consensus Framework for Evaluating Banking-Sector NIDS Dataset Coverage of MITRE ATT&CK Techniques

arXiv:2608.00895v1 Announce Type: new Abstract: The systemic criticality of global banking networks has ren-dered them high-priority targets for advanced persistent threats, neces-sitating Network Int…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Explainable Hybrid Feature Selection for Intrusion Detection in Internet of Medical Things Environments

arXiv:2608.00869v1 Announce Type: new Abstract: Internet of Medical Things (IoMT) networks are hard to protect: devices are heterogeneous, computing resources are scarce, and traffic must be analyzed …

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
XR-PRISM: Data-Driven Privacy and Risk Impact Scoring Metric for Extended Reality in Healthcare

arXiv:2608.00826v1 Announce Type: new Abstract: Extended Reality (XR) technologies are transforming healthcare through immersive training, remote consultation, and patient rehabilitation. However, the…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Hardware-rooted attestation for AI-agent evidence: composing IETF RATS with action evidence packages

arXiv:2608.00801v1 Announce Type: new Abstract: An action evidence package (AEP) is a signed, append-only record of what an AI agent did, who or what authorised the action, and what the outcome was. I…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Safety Invariants for Agents Orchestrating Irreversible State Transitions: A Four-Dimensional Formalism Evaluated on Public Ledgers

arXiv:2608.00783v1 Announce Type: new Abstract: Autonomous agents are increasingly asked to produce irreversible effects on external systems - transferring funds, writing to durable storage, actuating…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Adversarial Attacks in Multi-Agent LLM Pipelines: Unveiling Structural Vulnerabilities in Agentic AI Architectures

arXiv:2608.00718v1 Announce Type: new Abstract: Multi-agent LLM pipelines orchestrate multiple specialized language model agents into structured workflows where intermediate outputs are passed across …

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Supporting Cybersecurity Risk Management for Medical Devices via the SECUMAN Ontology and Shapes

arXiv:2608.00698v1 Announce Type: new Abstract: We propose the SECUMAN ontology and shapes for representing and analysing cybersecurity risk-management documentation for medical devices. Cybersecurity…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
From Chasing Ghosts to Missed Attacks: Perspectives and Perceptions of SOC Practitioners on LLM Integration, Risks, and Readiness

arXiv:2608.00672v1 Announce Type: new Abstract: Security Operations Centers (SOCs) process large volumes of security events, requiring analysts to accurately detect and assess ongoing cyberattacks und…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Improving the Security of Containerized Workloads using Transparency and Traceability Services

arXiv:2608.00660v1 Announce Type: new Abstract: Containerized workloads are commonly built via CI/CD pipelines, stored in registries, and executed across heterogeneous infrastructures, including cloud…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Domain Decoupling Attack: Exploiting the Validation Gap Between Protective DNS and Shared Edge Routing

arXiv:2608.00643v1 Announce Type: new Abstract: Network attackers often conceal malicious communication within legitimate Internet traffic. Existing CDN-based evasion techniques rely on SNI--Host inco…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
A False Average: Chain-of-Thought Monitors Collapse Where They Are the Only Defense

arXiv:2608.00583v1 Announce Type: new Abstract: Chain-of-thought (CoT) monitoring is meant to catch the reward hacks that look clean in the actions and betray themselves only in the reasoning. We show…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Robust Watermarks Meet Backdoored Models: Evading Diffusion Semantic Watermarks via Stealthy Backdoor

arXiv:2608.00543v1 Announce Type: new Abstract: Although semantic watermarking is considered a promising safeguard for images generated by Latent Diffusion Models (LDMs), the reliance of the watermark…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Exploring Usability and Legal Practice: Insights from German Judicial Users of Digital Forensics

arXiv:2608.00541v1 Announce Type: new Abstract: Digital forensics has become an integral part of modern criminal proceedings, yet its effective integration remains challenging because of increasing da…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Auditable Release Control for Pedagogical Leakage in LLM Tutors

arXiv:2608.00515v1 Announce Type: new Abstract: Large language model tutors can be correct and helpful yet disclose an answer or decisive reasoning before that disclosure is authorized. We formalize t…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
TI-StegoAlign: Channel-Guided Post-Training for Generative Text Steganography under Tokenization Inconsistency

arXiv:2608.00382v1 Announce Type: new Abstract: Generative text steganography enables LLM agents to exchange secret information through task-relevant messages. Yet most methods evaluate recovery on se…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Trimming: Decoupling Multiplicative Depth from Modulus Chains in RNS-CKKS via Rational Levels

arXiv:2608.00375v1 Announce Type: new Abstract: Recent work on Grafting decouples scale factors from ciphertext moduli, enabling more flexible precision management in RNS-CKKS. However, the multiplica…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Reflection, Education, Consistency: Towards Best Ethics Practices At Security And Privacy Conferences

arXiv:2608.00282v1 Announce Type: new Abstract: Research ethics is a controversial and emotionally charged topic in the security and privacy community, sparking discussions at conferences and on socia…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
From Monoliths to Swarms: A Study of Attack Surface Evolution in the Transition to Multi-Agent Web Systems

arXiv:2608.00202v1 Announce Type: new Abstract: Large Language Model (LLM)-based web agents are increasingly evolving from single-agent systems (SAS) to multi-agent systems (MAS). While MAS can lead t…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Exposed by Design: A Dynamic Security Assessment of Internet-Facing MCP Servers at Scale

arXiv:2608.00150v1 Announce Type: new Abstract: The Model Context Protocol (MCP) has seen rapid adoption since its November 2024 launch, with over 21,000 server instances detectable on the public inte…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Symbolic Attack Chain Generation from Atomic Red Team Techniques: An Empirical Study of Predicate Representation Granularity

arXiv:2608.00143v1 Announce Type: new Abstract: Automated attack chain generation is critical for modern cybersecurity, yet manual construction fails to scale as adversary behaviors expand. While clas…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Stateful Cooperative Agents Safeguarding LLMs Against Evolving Multi-Turn Attacks

arXiv:2608.00134v1 Announce Type: new Abstract: As LLMs become increasingly integrated into complex applications, their vulnerability to adversarial attacks has raised significant concerns. However, e…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Enforcing Access Control in Distributed Version Control Systems

arXiv:2608.00132v1 Announce Type: new Abstract: Version control systems (VCS), including central VCS (CVCS) and distributed VCS (DVCS), are widely adopted to manage the changes to various types of dat…

arXiv Security Read →
◬ AI & Machine Learning Aug 04, 2026
Deep Learning for Cyber Threat Detection and Mitigation in Healthcare-IoT

arXiv:2608.00118v1 Announce Type: new Abstract: Cybersecurity is a fundamental requirement for protecting wearable devices used in healthcare Internet of Things (H-IoT) systems. Security failures in t…

arXiv Security Read →
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