Privacy-preserving Outsourced Computation

The Centre for Doctoral Training in Cyber Security for the Everyday at Royal Holloway seeks to recruit a PhD student to work on privacy-preserving outsourced computation techniques. This project will be carried out jointly with KDDI Research, Japan.

The research in this project will focus on the design, analysis and implementation of efficient privacy-preserving cryptographic techniques and their applications. Secure computation methods enable the computation on encrypted data without decryption. Main cryptographic techniques for constructing secure computation schemes include homomorphic encryption, multi-party computation, private set operation protocols and functional encryption. In this project, the student will consider secure computation applications, for example privacy-preserving cybersecurity analysis. Cybersecurity systems (e.g. IDS, IPS) typically collect large amounts of data in order to detect security events or anomaly events. Analysis of this data may however pose a significant threat to the privacy of users. A privacy-preserving cybersecurity system attempts to alleviate this threat by carrying out the analysis over encrypted data. The goal of the project is to research the design and security of privacy-preserving cybersecurity systems, and may consider (among other research problems) the enhancement for the basic secure computation techniques, their optimisation for computation over large datasets, as well as novel applications.

The Information Security Group (ISG) at Royal Holloway has a strong track record in cryptographic research, including algorithm design and analysis, post-quantum cryptography, homomorphic encryption and applications of secure computation. KDDI Research is the research and innovation arm of KDDI Corporation, one of the largest Japanese telecommunications operators. The ISG and KDDI have a long-term collaboration in the area of cryptography, and the student recruited for this project will work closely with researchers from the two groups.

Applicants are expected to have a background in mathematics, computer science, or a related discipline. Prospective applicants are welcome to contact Professor Carlos Cid (carlos.cid@rhul.ac.uk) to discuss the project.