Conferences - Seminars
Data compression and secrecy by design
By Dr. Yanina Shkel, Princeton 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.
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. Time permitting, we will also discuss connections between secrecy by design and related
notions such as randomness extraction and common information.
Organization IPG Seminar
Accessibility Informed public