Privacy-preserving and trusted threat intelligence sharing using distributed ledgers

Ali, Hisham Mahmoud Alhassan

Abstract

In the dynamic landscape of cybersecurity, organisations face increasingly sophisticated and emerging threats, highlighting the need for secure and collaborative threat intelligence sharing platforms. This PhD research identifies key shortcomings in existing solutions and proposes an innovative permissioned ledger-based sharing infrastructure to create a trustworthy ecosystem for secure and trusted threat intelligence sharing.
Increasing cyberattacks, stricter regulations, and limitations in traditional threat information systems highlight the need for innovative solutions. Centralised systems are vulnerable to single points of failure and unauthorised access, raising privacy concerns and hindering the creation of collaborative relationships. Analysis of literature and expert and stakeholder feedback emphasizes these issues and the critical need for a more secure, efficient, and collaborative threat sharing platform.
This research introduces a permissioned ledger-based infrastructure to address these issues. It utilises advanced technologies and a novel cryptographic method featuring attributes like time-bombing, time-revealing, location-locking, and message redaction to enhance secure information exchange and foster cross-organisational collaboration.
The thesis’ key contributions include the development and implementation of a robust infrastructure using Hyperledger Fabric, Ciphertext-Policy Attribute-Based Encryption (CP-ABE), Interplanetary File System (IPFS), the MITRE ATT&CK framework, Large LanguageModels (LLMs), and Structured Threat Information Expression (STIX). Evaluation and use cases, such as IoT data control, demonstrate the system’s effectiveness in enhancing security, scalability, and efficiency.
Intensive testing shows substantial advances in security and collaboration, underlining the importance of secure and trusted information exchange. Future research will explore integrating advanced AI technologies, refining consensus mechanisms, and addressing legal and ethical considerations to further enhance the system’s capabilities and applications in cybersecurity.

Citation

Ali, H. M. A. Privacy-preserving and trusted threat intelligence sharing using distributed ledgers. (Thesis). Edinburgh Napier University

• Thesis Type: Thesis
• Deposit Date: Jan 6, 2025
• Publicly Available Date: Jan 6, 2025
• DOI: https://doi.org/10.17869/enu.2024.4043796
• Award Date: Oct 31, 2024