Application-Tailored Security: Lessons from Theory to Practice

Speaker: Mohammed Karmoose
Affiliation: UCLA Ph.D. Candidate

Abstract: With the increase of inter-connected devices, it is of paramount importance to ensure the security of the exchanged information. While cryptographic techniques provide tools to provide confidentiality and data integrity, such techniques may not be the most efficient solutions. In addition, applications today have challenging performance requirements, with the emergence of time-critical applications such as vehicle networks, as well as resource-limited inter-connected devices such as the devices used in the Internet-of-Things. For such applications, novel security solutions that are application-tailored are needed to meet the performance requirements while adhering to the constraints imposed by the available resources. In this thesis, we adopt this methodology for security design: by understanding the nature of the application, the possible adversaries that may target the communication system, as well as the performance requirements, we design suitable and efficient security solutions. We show this methodology in the context of three different scenarios.

The first scenario is data broadcasting in the context of the index coding problem. We study the problem of providing privacy guarantees against curious clients who are interested in knowing the requests and side information sets of other clients. We first design index codes with higher privacy levels than conventional index codes. We also provide a mechanism, which we call k-limited-access schemes, which transforms any index coding technique into another code with higher privacy guarantees. The second scenario is in the context of communication systems which relies on millimeter waves. We tackle the problem of secret key establishment. We propose a secret key establishment protocol which allows two communicating parties to establish shared secret keys at very high rates. We showcase the performance of our proposed technique in two different applications: in millimeter wave wireless systems such as 5G networks and IEEE 802.11ay, and vehicle platooning. The last scenario is in the context of Cyber-Physical Systems. We first argue that, in many situations, an adversary is interested in learning the state vector of the control system. In such cases, a more suitable security metric would be a distortion-based one which leads the adversary to make state estimates that are far from the actual value. We then propose security schemes that require a very small number of secret key bits and still perform well according to the proposed metric: we show that our proposed schemes are in fact optimal for many cases.

Biography: Mohammed Karmoose is a Ph.D. student in the ECE Department at UCLA. He received his B.S. and M.S. degrees in Electrical and Electronics Engineering from Alexandria University in 2009 and 2013, respectively. He has also been an intern in the Security Research Group at Intel Labs in 2017. He received the Annual Distinguished Student Award from Alexandria University for the years 2005 to 2009. His research interests include information theory, security and privacy in communication and cyber-physical systems, and distributed detection.

For more information, contact Prof. Christina Fragouli ()

Date(s) - Jun 12, 2019
12:00 pm - 2:00 pm

E-IV Faraday Room #67-124
420 Westwood Plaza - 6th Flr., Los Angeles CA 90095