@inproceedings{fc6c6bb0d2db4c5ead444d538419173a,
title = "Security design for NLIP: A universal protocol for AI-enabled systems",
abstract = "NLIP or Natural Language Interaction Protocol is being defined by a group of researchers that enables a universal, standards-based application-level protocol to work across AI Enabled Services. NLIP leverages the capabilities of large language models to transform unstructured natural language to a structured representation at the endpoints, replacing multiple individual application protocols with a single one. The design of such a protocol must necessarily include security considerations, paying significant attention to protocol integrity, privacy, data governance and cybersecurity defenses. In this paper we discuss the approaches we have introduced to maintain these security elements of the protocol. The security of the protocol requires not only taking into consideration the needs of communication flow on the wire, but also to handle the security requirements of the endpoints. This requires appropriate support for functions like authentication and authorization, where some of these services can be provided by a third-party service provider. Furthermore, many existing security protocols and paradigms are already supported by existing software services which NLIP may utilize which we need to be able to leverage them at server endpoints. An application-level protocol needs to leverage existing services while still ensuring adequate security at the application level. We discuss the challenges in designing security for an application-level protocol like NLIP and discuss how we have addressed these problems to ensure a secure implementation of NLIP.",
author = "Sanjay Aiyagari and Elisa Bertino and Jan Bienik and Chiou, \{Yan Ming\} and Raj Dodhiawala and Sean Hughes and Sugih Jamin and Ashish Kundu and Jonathan Lenchner and Mauriello, \{Matthew Louis\} and Abhay Ratnaparakhi and Mohamed Rahouti and Tom Sheffler and Shen, \{Chien Chung\} and Dinesh Verma and Jinjun Xiong and Luyi Xing and Wenpeng Yen and Hasan Zengin",
note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; Assurance and Security for AI-Enabled Systems 2025 ; Conference date: 14-04-2025 Through 16-04-2025",
year = "2025",
doi = "10.1117/12.3055287",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Harguess, \{Joshua D.\} and Bastian, \{Nathaniel D.\} and Pace, \{Teresa L.\}",
booktitle = "Assurance and Security for AI-Enabled Systems 2025",
address = "United States",
}