Paper Details

Name: Rahul Bhardwaj, Pooja, Ritik Raushan, Akanksha Jain & Azhar Ashraf Gadoo
Country: India

Year: 2026
Volume: Volume No: 13, January, Year: 2026 (Special Issue)
Page Number: 168-176
DOI: https://doi.org/10.5281/zenodo.18975549

ABSTRACT –
Cybersecurity threats have become quite sophisticated, and organizations depend on real-time threat intelligence sharing to protect themselves against the rise of attacks. However, privacy, data confidentiality and competitive risks often restrict their collaboration to the data exchange only. In this paper one, we present a privacy-preserving threat-sharing framework
allowing parties to exchange sensitive threat intelligence information while preventing sensitive internal information leak. only get access to the raw data, while aggregated threat data can be shared with lead analytics. We explore its applicability in threat-sharing within varying contexts, showing organizations manners of leveraging aggregated intelligence without
revealing avenues for proprietary or sensitive data compromise. We show that the use of privacy-preserving mechanisms can greatly facilitate cross-organizational collaboration for cybersecurity and can be compliant with regulatory and legal obligations. This paper provides insights into the broader discussion of secure cyber defence strategies, stressing the role of privacy in promoting collaboration against cyber threats.

Keywords: Cybersecurity, Threat Intelligence Sharing, Privacy-Preserving Framework, Cryptographic Techniques, Differential Privacy, Secure Multi-Party Computation (MPC), Cross- Organizational Collaboration.