Secure aggregation of sufficiently many private inputs.

Area of Science:

• Cryptography and Information Security
• Cybersecurity
• Distributed Systems

Background:

• Secure aggregation of distributed data is crucial but challenging.
• Existing methods often lack robust anonymity guarantees.
• Cyber Threat Intelligence (CTI) requires secure and private data sharing.

Purpose of the Study:

• To design and implement an efficient cryptographic protocol for secure and anonymous aggregation.
• To ensure input privacy by implementing a minimal quota system before outcome publication.
• To demonstrate the protocol's applicability in the CTI domain.

Main Methods:

• Development of an efficient cryptographic protocol for secure aggregation.
• Implementation of a minimal quota mechanism to guarantee anonymity.
• Testing the protocol's performance and security in a simulated CTI environment.

Main Results:

• The protocol successfully achieves secure and anonymous aggregation of distributed inputs.
• Performance benchmarks show three secure aggregations per second with 20 inputs.
• Scalability demonstrated with potential for 10,000 aggregations overnight in a 100-partner CTI community.

Conclusions:

• The proposed protocol offers an efficient solution for secure and anonymous data aggregation.
• The minimal quota system effectively enhances input privacy.
• The protocol is well-suited for practical applications in CTI and other domains requiring secure data fusion.