arXiv:2510. 20692v3 Announce Type: replace-cross Abstract: Access control policies are reliability-critical configuration artifacts in cloud systems, yet administrators frequently struggle to verify that a policy permits exactly what they intend.
By Adarsh Vatsa, Bethel Hall, William Eiers
arXiv:2607. 15987v1 Announce Type: new Abstract: The ODRL policy language is emerging as the de-facto standard for policy modelling data access and usage preferences, AI governance policies and data workflows in European dataspaces.
By Jaime Osvaldo Salas, Paolo Pareti, Adeel Aslam, Christopher Maidens, George Konstantinidis
arXiv:2606. 19464v1 Announce Type: new Abstract: Autonomous agentic AI systems driven by Large Language Models (LLMs) introduce a new class of security, privacy, and compliance challenges: an agent that can invoke tools, manipulate data, install software, and coordinate with peer agents across organizational boundaries must be constrained not just by authentication and access control, but by the full structure of enterprise governance.
By Anupam Joshi, Tim Finin, Karuna Pande Joshi, Lalana Kagal
arXiv:2607. 03656v1 Announce Type: cross Abstract: Large Language Models are increasingly used to turn natural-language requirements into code.
By Adarsh Vatsa, Sachi Shome, Yingming Zhou, William Eiers
arXiv:2606. 04769v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) has emerged as a critical standard empowering Large Language Models (LLMs) to utilize external tools.
By Yutao Shi, Xiaohan Zhang, Xiangjing Zhang, Xihua Shen, Hui Ouyang, Huming Qiu, Mi Zhang, Min Yang
arXiv:2604. 01039v2 Announce Type: replace-cross Abstract: System Instructions in Large Language Models (LLMs) are commonly used to enforce safety policies, define agent behavior, and protect sensitive operational context in agentic AI applications.
By Anubhab Sahu, Diptisha Samanta, Reza Soosahabi