"Data Compression and Secrecy by Design"

Yanina Shkel, Faculty Candidate, Princeton University

February 26th (Tuesday), 3:00pm
Harold Frank Hall (HFH), Rm 4164 (ECE Conf. Rm.)

The unique characteristics of the IoT make it very challenging to provide adequate security primitives. The complexity of traditional cryptographic methods is an issue for IoT applications that have very stringent delay requirements. Moreover, in the context of the IoT, security requirements and the explicit applications have to be taken into account from the beginning of the protocol design. Motivated by these unique characteristics of the IoT systems, we introduce the framework of secrecy by design as an approach to partial information-theoretic secrecy. The main idea behind secrecy by design is to begin with an operational secrecy constraint, which is modeled by a secrecy function, and then to derive fundamental limits for the performance of the resulting secrecy system. In the setting of lossless compression, we show that strong information-theoretic secrecy guarantees can be achieved using a reduced secret key size and a modular two-part coding strategy. Moreover, the proposed two-part codes possess a universality property that has an immediate implication for secure inference. We will end by discussing how the techniques developed in this work could be adopted to other problems such as mitigating timing side-channel attacks. Time permitting, we will review emerging trends at the intersection of data compression and learning theory, as well as random access and low latency communication.

About Yanina Shkel:

Yanina Shkel is a research scholar in the department of Electrical Engineering at Princeton University. Yanina has B.S. degrees in Mathematics and in Computer Science, as well as a Ph.D. degree in Electrical and Computer Engineering from University of Wisconsin-Madison. Before attending graduate school she worked as a developer for Morningstar, Inc. where she administered databases containing and processing large amounts of financial data. More recently, she was an intern at 3M Corporate Research Labs where she had a unique opportunity to apply her background in computation and information sciences for materials and product driven needs of 3M. Yanina is a recipient of the NSF Center for Science of Information (CSoI) postdoctoral fellowship.