Advances in homomorphic encryption for privacy-preserving data analytics

Rafferty, C. (Advisor)

Activity: Talk or presentation typesInvited talk

Description

In this session, the concept of privacy enhancing technologies (PETs) will be introduced and some exciting research and development in this field will be highlighted. One promising type of PETs, homomorphic encryption, will be discussed in more detail, covering introductory concepts, as well as some recent practical developments and future directions in this field.

Fully homomorphic encryption (FHE), introduced in 2009, enables secure computation on encrypted data, without the need for decryption. FHE is seen as a massively powerful tool, which could revolutionise secure cloud computation, but unfortunately it is accompanied with highly expensive implementation costs, in terms of practicality. Current trends in homomorphic encryption will be discussed alongside its contribution to privacy-preserving data analytics, alongside other important techniques in privacy-preserving data analytics. The talk will conclude with a snapshot of our latest research into HE for data analytics.
Period28 Jul 2021
Held atThe London Office for Rapid Cybersecurity Advancement (LORCA), United Kingdom
Degree of RecognitionNational