Introduction to Homomorphic Encryption and Its Applications to Privacy Preserving Data/Signal Analysis


Cryptography has been an integral part of Internet communications for many decades. However, with regard to processing received or sent data, it should be decrypted first. In this session, concepts of homomorphic encryption (HE) that allow for direct computation over encrypted data will be introduced. Recently, a number of practical HE schemes have been developed by Microsoft and other Tech Giants that in turn sped up the adaption of HE by cloud computing services. The session begins by providing the definition of homeomorphism that is supplemented by an example of an HE scheme that relies on the factorization difficulty of a number into its prime. Then we proceed to implementing a machine learning algorithm over encrypted data using CKKS scheme, the limitations of this scheme also presented. Further two practical applications of HE will be described: a trading algorithm that generates a buy or sell decision on encrypted data and a medical application that illustrates a potential use of HE in controlling insulin in diabetic patients.


Name: Artem Lenskiy
Bio :

Artem Lenskiy received his PhD in Electrical Engineering from the University of Ulsan, South Korea with the funding by the Agency for Defense Development, and currently is finishing his second master’s degree in Applied Mathematics at Johns Hopkins. He has over 15 years of experience in data analysis, software development, and mathematical modelling. He consults government organisations, proprietary trading firms, and has delivered projects for the Department of Defence, the Department of Health and the Department of Industry Science Energy and Resources. Artem has published in numerous journals on homomorphic encryption, algorithmic trading, and machine learning, and given talks on these topics at Australian universities, IPAA ACT, and several private organisations. He has also taught over 15 computer science and math courses at the undergraduate and graduate levels. He is currently supervising over 10 graduate students at the ANU. In his spare time, he enjoys riding a bicycle, swimming, and math blogging.

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