학술논문

Forensic Insights From Smartphones Through Electromagnetic Side-Channel Analysis
Document Type
Periodical
Source
IEEE Access Access, IEEE. 9:13237-13247 2021
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Smart phones
Forensics
Mathematical model
Cameras
Performance evaluation
Data acquisition
Computational modeling
Digital forensics
smartphone forensics
electromagnetic side-channel
software behaviour detection
deep learning model
Language
ISSN
2169-3536
Abstract
The increasing use of smartphones has increased their presence in legal and corporate investigations. Unlike desktop and laptop computers, forensic analysis of smartphones is a challenging task due to their limited interfaces to retrieve information of forensic value. Electromagnetic side-channel analysis (EM-SCA) has been recently proposed as an alternative window to acquire forensic insights from computers, in particularly from Internet of Things devices. Along this line, this work experimentally evaluates the potential of extracting information of forensic value from smartphones through their EM radiation. Initially, a group of smartphones representing a diverse set of system-on-chip (SoC) processors were used to acquire EM radiation traces. Later, deep learning models were trained to detect various internal software behaviours running on the SoCs. The results of this work indicates that a wide variety of insights can be extracted from smartphones through EM side-channel, increasing the potential opportunities for digital forensic investigators.