Monitoring Software Execution Flow Through Power Consumption and Dynamic Time Warping

Vidal, Boris; Moreno, Carlos

Abstract

This letter presents a technique for nonintrusive code execution tracking using side-channel signals of power consumption. Using a nearest-neighbor classifier that integrates the dynamic time warping distance with information from the control flow graph, it is possible to identify executed basic blocks from a trace of power consumption that exhibits temporal distortions due to assembly-level artifacts and varying operational conditions. Experimental results show that the proposed technique achieves over 95% precision when inferring the runtime execution flow of a cruise control application using unmarked traces of power consumption collected from different processors. © 2009-2012 IEEE.

Más información

Título según WOS: Monitoring Software Execution Flow Through Power Consumption and Dynamic Time Warping
Título según SCOPUS: Monitoring Software Execution Flow Through Power Consumption and Dynamic Time Warping
Título de la Revista: IEEE Embedded Systems Letters
Volumen: 15
Número: 2
Editorial: Institute of Electrical and Electronics Engineers Inc.
Fecha de publicación: 2023
Página de inicio: 101
Página final: 104
Idioma: English
DOI:

10.1109/LES.2022.3197092

Notas: ISI, SCOPUS