Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform.

Area of Science:

• Cybersecurity
• Information Security
• Distributed Ledger Technology

Background:

• Traditional threat information sharing is inefficient and insecure.
• Organizational vulnerabilities change, necessitating dynamic risk assessment.
• Threat intelligence technology is crucial for detecting and sharing cyberattack tactics.

Purpose of the Study:

• To propose a privacy-preserving mechanism for trusted threat information sharing.
• To enhance organizational security and automation through improved data sharing.
• To establish a reliable and secure architecture for data automation, quality, and traceability.

Main Methods:

• Utilizing blockchain smart contracts and Interplanetary File System (IPFS) for data sharing.
• Implementing Hyperledger Fabric, a private-permissioned distributed ledger technology.
• Integrating the MITRE ATT&CK threat intelligence framework for threat classification and analysis.

Main Results:

• The proposed system offers a reliable and secure architecture for threat intelligence.
• Enhanced data automation, quality, and traceability in cybersecurity event sharing.
• Improved defensive capabilities against unknown cyberattacks through trusted partner collaboration.

Conclusions:

• The blockchain and IPFS combination enhances organizational system reliability and security.
• The methodology provides a privacy-preserving and trusted approach to threat information sharing.
• This approach can be extended to combat intellectual property theft and industrial espionage.