In the era of small devices connected to each other and to the cloud, security in both hardware and software is of high importance. This work takes on the market demands of the "Internet of Things" devices and proposes the smallest hardware crypto core that is immune to side-channel attacks, improving the previous by almost 15%. On the software side, this work takes a first step into proving that by simply measuring certain hardware performance counters, or by monitoring certain hardware resources, it is possible to accurately identify codes during their execution. Because of their high criticality, this work uses crypto codes and tries to identify them using machine learning techniques. In a simulated environment, an accuracy of over 90% is achieved in classifying crypto algorithms.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Pavel, Laurentiu

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-032516-112132

Advisor

• Eisenbarth, Thomas

Year

• 2016

Date created

• 2016-03-25

Resource type

• Major Qualifying Project

Major

• Interdisciplinary

Rights statement

• In Copyright