WEDNESDAY July 22, 2:00pm - 3:30pm
TOPIC AREA: SECURITY, MACHINE LEARNING/AI
KEYWORD: HARDWARE SECURITY, SECURITY & PRIVACY, SYSTEM SECURITY
EVENT TYPE: SPECIAL/INVITED SESSION
Machine Learning Based Side-Channel Attacks and Countermeasures for IoT Systems
Chairs:
Inna Partin-Vaisband - Univ. of Illinois at Chicago, IL
Selçuk Köse - Univ. of Rochester, Rochester, NY
Organizers:
Inna Partin-Vaisband - Univ. of Illinois at Chicago, IL
Selcuk Kose - Univ. of Rochester, Rochester, NY
This session covers two closely related topics of increasing importance to the security of IoT systems: (1) Machine Learning (ML) based attacks, monitoring, and countermeasures for physical power and electromagnetic (EM) side-channel attacks (SCAs) on crypto accelerators embedded in IoT edge devices; and (2) ML attacks against strong Physically Unclonable Function (PUF) based digital authentication of IoT devices and ML attack-resistant strong-PUF design. The speakers discuss the security challenges, needs, and ML-based trust methods relevant to this fast-developing world of IoT. The first talk gives an overview of the key challenges and research directions in this area, and covers recent results on ML-based monitoring of side-channel attacks. The second talk covers countermeasures against physical power and EM SCAs for crypto accelerators. The final talk from Intel presents ML attacks against strong-PUF based authentication and attack-resistant strong PUF designs.

44.1Machine Learning Based Side Channel Attacks and Countermeasures
 Speaker: Marilyn Wolf - Univ. of Nebraska, Lincoln, NE
 Authors: Dimitrios Serpanos - Univ. of Patras, Patras, Greece
Shengqi Yang - Beijing Univ. of Technology, Beijing, China
Marilyn Wolf - Univ. of Nebraska, Lincoln, NE
44.2Countermeasures Against Physical Power and EM Side-Channel Attacks for Crypto Accelerators
 Speaker: Saibal Mukhopadhyay - Georgia Institute of Technology, Atlanta, GA
 Authors: Arvind Singh - Cryptography Research, Inc.
Monodeep Kar - Intel Corp., Hillsboro, OR
Nael Mizanur Rahman - Georgia Institute of Technology, Atlanta , GA
Nikhil Chawla - Georgia Institute of Technology, Atlanta , GA
Saibal Mukhopadhyay - Georgia Institute of Technology, Atlanta, GA
44.3A 0.26% BER, Machine-Learning Resistant 1028 Challenge-Response PUF in 14nm CMOS Featuring Stability-Aware Adversarial Challenge Selection
 Speaker: Sanu K. Mathew - Intel Corp., Hillsboro, OR
 Authors: Vikram Suresh - Intel Corp., Hillsboro, OR
Raghavan Kumar - Intel Corp., Hillsboro, OR
Sanu K. Mathew - Intel Corp., Hillsboro, OR