arXiv:2603.23171v1 Announce Type: new Abstract: Large language models (LLMs) can be misused to reveal sensitive information, such as weapon-making instructions or writing malware. LLM providers rely o…
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arXiv:2603.23171v1 Announce Type: new Abstract: Large language models (LLMs) can be misused to reveal sensitive information, such as weapon-making instructions or writing malware. LLM providers rely o…
arXiv:2603.23117v1 Announce Type: new Abstract: By integrating Chain-of-Thought(CoT) reasoning, Vision-Language-Action (VLA) models have demonstrated strong capabilities in robotic manipulation, parti…
arXiv:2603.23064v1 Announce Type: new Abstract: We identify a critical security vulnerability in mainstream Claw personal AI agents: untrusted content encountered during heartbeat-driven background ex…
arXiv:2603.23012v1 Announce Type: new Abstract: Critical energy infrastructures increasingly rely on information and communication technology for monitoring and control, which leads to new challenges …
arXiv:2603.23007v1 Announce Type: new Abstract: The rapid adoption of mobile graphical user interface (GUI) agents, which autonomously control applications and operating systems (OS), exposes new syst…
arXiv:2603.23005v1 Announce Type: new Abstract: Steganography conceals secret information within innocuous carriers while preserving visual fidelity and enabling reliable recovery. Recent unified netw…
arXiv:2603.22987v1 Announce Type: new Abstract: Membership inference attacks (MIAs) aim to determine whether a data sample was included in a machine learning (ML) model's training set and have become …
arXiv:2603.22982v1 Announce Type: new Abstract: Provenance-based Intrusion Detection Systems (PIDSes) have been widely used to detect Advanced Persistent Threats (APTs). Although many studies achieve …
arXiv:2603.22968v1 Announce Type: new Abstract: The growing use of large language models has increased interest in sharing textual data in a privacy-preserving manner. One prominent line of work addre…
arXiv:2603.22954v1 Announce Type: new Abstract: Electronic health records (EHRs) and other real-world clinical data are essential for clinical research, medical artificial intelligence, and life scien…
arXiv:2603.22928v1 Announce Type: new Abstract: Recent AI systems combine large language models with tools, external knowledge via retrieval-augmented generation (RAG), and even autonomous multi-agent…
arXiv:2603.22868v1 Announce Type: new Abstract: Agentic computing systems, which autonomously spawn new functionalities based on natural language instructions, are becoming increasingly prevalent. Whi…
arXiv:2603.22853v1 Announce Type: new Abstract: What should a developer inspect before deploying an LLM agent: the model, the tool code, the deployment configuration, or all three? In practice, many s…
arXiv:2603.22808v1 Announce Type: new Abstract: We introduce PolyVeil, a protocol for private Boolean summation across $k$ clients that encodes private bits as permutation matrices in the Birkhoff pol…
arXiv:2603.22771v1 Announce Type: new Abstract: As the Internet of Things (IoT) continues to expand across critical infrastructure, smart environments, and consumer devices, securing them against cybe…
arXiv:2603.22751v1 Announce Type: new Abstract: Large language model (LLM) agents may expose sensitive information through more than their final textual responses. Whenever private content is internal…
arXiv:2603.22717v1 Announce Type: new Abstract: Automatically generating source code from natural language using large language models (LLMs) is becoming common, yet security vulnerabilities persist d…
arXiv:2603.22685v1 Announce Type: new Abstract: We present BlindMarket, an end-to-end zero-trust distribution framework for hardware IP cores. BlindMarket allows two parties, the IP user and the IP ve…
arXiv:2603.22612v1 Announce Type: new Abstract: The rapid advancement of Large Language Models (LLMs) in biological research has significantly lowered the barrier to accessing complex bioinformatics k…
arXiv:2603.22603v1 Announce Type: new Abstract: Traditional threat modeling occurs during design, but cloud deployments introduce unanticipated threats, especially multi-stage attacks chaining vulnera…
arXiv:2603.22577v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated potential in code generation, yet they struggle with the multi-step, stateful reasoning required for offe…
arXiv:2603.22511v1 Announce Type: new Abstract: Capture The Flag (CTF) competitions have established themselves as a highly effective pedagogical tool in cybersecurity education, offering students han…
arXiv:2603.22499v1 Announce Type: new Abstract: Synthetic insider threat benchmarks face a consistency problem: corpora generated without an external factual constraint cannot rule out cross-artifact …
arXiv:2603.22489v1 Announce Type: new Abstract: The Model Context Protocol (MCP) has rapidly emerged as a universal standard for connecting AI assistants to external tools and data sources. While MCP …