Cyber Threat Intelligence Sharing: A Privacy-Preserving Framework for Cross-Organization Collaboration

Abstract

This paper explores a privacy-preserving framework for cross-organization collaboration in cyber threat intelligence sharing. The proposed framework aims to enhance collective defense against cyber threats by facilitating information exchange among organizations while ensuring the privacy and security of shared data. By integrating advanced cryptographic techniques and privacy-preserving mechanisms, the framework addresses key challenges in threat intelligence sharing, including data confidentiality, integrity, and trust.