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🔥 Trending Topics · Last 48h
◬ AI & Machine Learning Apr 08, 2026
Pramana: Fine-Tuning Large Language Models for Epistemic Reasoning through Navya-Nyaya

arXiv:2604.04937v1 Announce Type: new Abstract: Large language models produce fluent text but struggle with systematic reasoning, often hallucinating confident but unfounded claims. When Apple researc…

arXiv AI Read →
◬ AI & Machine Learning Apr 08, 2026
The Hiremath Early Detection (HED) Score: A Measure-Theoretic Evaluation Standard for Temporal Intelligence

arXiv:2604.04993v1 Announce Type: cross Abstract: We introduce the Hiremath Early Detection (HED) Score, a principled, measure-theoretic evaluation criterion for quantifying the time-value of informat…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
Measuring the Permission Gate: A Stress-Test Evaluation of Claude Code's Auto Mode

arXiv:2604.04978v1 Announce Type: cross Abstract: Claude Code's auto mode is the first deployed permission system for AI coding agents, using a two-stage transcript classifier to gate dangerous tool c…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
Towards Predicting Multi-Vulnerability Attack Chains in Software Supply Chains from Software Bill of Materials Graphs

arXiv:2604.04977v1 Announce Type: cross Abstract: Software supply chain security compromises often stem from cascaded interactions of vulnerabilities, for example, between multiple vulnerable componen…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
Who Governs the Machine? A Machine Identity Governance Taxonomy (MIGT) for AI Systems Operating Across Enterprise and Geopolitical Boundaries

arXiv:2604.06148v1 Announce Type: new Abstract: The governance of artificial intelligence has a blind spot: the machine identities that AI systems use to act. AI agents, service accounts, API tokens, …

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
Towards Securing IIoT: An Innovative Privacy-Preserving Anomaly Detector Based on Federated Learning

arXiv:2604.06101v1 Announce Type: new Abstract: In the light of the growing connectivity and sensitivity of industrial data, cyberattacks and data breaches are becoming more common in the Industrial I…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
Signature Placement in Post-Quantum TLS Certificate Hierarchies: An Experimental Study of ML-DSA and SLH-DSA in TLS 1.3 Authentication

arXiv:2604.06100v1 Announce Type: new Abstract: Post-quantum migration in TLS 1.3 should not be understood as a flat substitution problem in which one signature algorithm is replaced by another and de…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
LLM4CodeRE: Generative AI for Code Decompilation Analysis and Reverse Engineering

arXiv:2604.06095v1 Announce Type: new Abstract: Code decompilation analysis is a fundamental yet challenging task in malware reverse engineering, particularly due to the pervasive use of sophisticated…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
Inertial Mining: Equilibrium Implementation of the Bitcoin Protocol

arXiv:2604.06092v1 Announce Type: new Abstract: The value of proof-of-work cryptocurrencies critically depends on miners having incentives to follow the protocol. However, the Bitcoin mining protocol …

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
CritBench: A Framework for Evaluating Cybersecurity Capabilities of Large Language Models in IEC 61850 Digital Substation Environments

arXiv:2604.06019v1 Announce Type: new Abstract: The advancement of Large Language Models (LLMs) has raised concerns regarding their dual-use potential in cybersecurity. Existing evaluation frameworks …

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
A Formal Security Framework for MCP-Based AI Agents: Threat Taxonomy, Verification Models, and Defense Mechanisms

arXiv:2604.05969v1 Announce Type: new Abstract: The Model Context Protocol (MCP), introduced by Anthropic in November 2024 and now governed by the Linux Foundation's Agentic AI Foundation, has rapidly…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
Swiss-Bench 003: Evaluating LLM Reliability and Adversarial Security for Swiss Regulatory Contexts

arXiv:2604.05872v1 Announce Type: new Abstract: The deployment of large language models (LLMs) in Swiss financial and regulatory contexts demands empirical evidence of both production reliability and …

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
Stealthy and Adjustable Text-Guided Backdoor Attacks on Multimodal Pretrained Models

arXiv:2604.05809v1 Announce Type: new Abstract: Multimodal pretrained models are vulnerable to backdoor attacks, yet most existing methods rely on visual or multimodal triggers, which are impractical …

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
BodhiPromptShield: Pre-Inference Prompt Mediation for Suppressing Privacy Propagation in LLM/VLM Agents

arXiv:2604.05793v1 Announce Type: new Abstract: In LLM/VLM agents, prompt privacy risk propagates beyond a single model call because raw user content can flow into retrieval queries, memory writes, to…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
SoK: Understanding Anti-Forensics Concepts and Research Practices Across Forensic Subdomains

arXiv:2604.05770v1 Announce Type: new Abstract: Anti-forensics includes a growing set of techniques designed to obstruct forensic analysis. While cybercriminals increasingly rely on these methods, the…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
Hackers or Hallucinators? A Comprehensive Analysis of LLM-Based Automated Penetration Testing

arXiv:2604.05719v1 Announce Type: new Abstract: The rapid advancement of Large Language Models (LLMs) has created new opportunities for Automated Penetration Testing (AutoPT), spawning numerous framew…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
From Incomplete Architecture to Quantified Risk: Multimodal LLM-Driven Security Assessment for Cyber-Physical Systems

arXiv:2604.05674v1 Announce Type: new Abstract: Cyber-physical systems often contend with incomplete architectural documentation or outdated information resulting from legacy technologies, knowledge m…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
T2T: Captioning Smartphone Activities Using Mobile Traffic

arXiv:2604.05642v1 Announce Type: new Abstract: This paper studies the creation of textual descriptions of user activities and interactions on smartphones. Our approach of referring to encrypted mobil…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
Foundations for Agentic AI Investigations from the Forensic Analysis of OpenClaw

arXiv:2604.05589v1 Announce Type: new Abstract: Agentic Al systems are increasingly deployed as personal assistants and are likely to become a common object of digital investigations. However, little …

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
Understanding User Privacy Perceptions of GenAI Smartphones

arXiv:2604.05571v1 Announce Type: new Abstract: GenAI smartphones, which natively embed generative AI at the system level, are transforming mobile interactions by automating a wide range of tasks and …

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
AttnDiff: Attention-based Differential Fingerprinting for Large Language Models

arXiv:2604.05502v1 Announce Type: new Abstract: Protecting the intellectual property of open-weight large language models (LLMs) requires verifying whether a suspect model is derived from a victim mod…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
Can You Trust the Vectors in Your Vector Database? Black-Hole Attack from Embedding Space Defects

arXiv:2604.05480v1 Announce Type: new Abstract: Vector databases serve as the retrieval backbone of modern AI applications, yet their security remains largely unexplored. We propose the Black-Hole Att…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
MA-IDS: Multi-Agent RAG Framework for IoT Network Intrusion Detection with an Experience Library

arXiv:2604.05458v1 Announce Type: new Abstract: Network Intrusion Detection Systems (NIDS) face important limitations. Signature-based methods are effective for known attack patterns, but they struggl…

arXiv Security Read →
◬ AI & Machine Learning Apr 08, 2026
LanG -- A Governance-Aware Agentic AI Platform for Unified Security Operations

arXiv:2604.05440v1 Announce Type: new Abstract: Modern Security Operations Centers struggle with alert fatigue, fragmented tooling, and limited cross-source event correlation. Challenges that current …

arXiv Security Read →
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