Identifying Internet of Things software activities using deep learning-based electromagnetic side-channel analysis-Reference-Cited by-同舟云学术

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Identifying Internet of Things software activities using deep learning-based electromagnetic side-channel analysis

Published:2021-12 Issue: Volume:39 Page:301308
ISSN:2666-2817
Container-title:Forensic Science International: Digital Investigation
language:en
Short-container-title:Forensic Science International: Digital Investigation

Author:

Le Quan,Miralles-Pechuán Luis,Sayakkara Asanka,Le-Khac Nhien-An,Scanlon Mark

Publisher

Elsevier BV

Subject

Law,Medical Laboratory Technology,Computer Science Applications,Information Systems,Pathology and Forensic Medicine

Reference39 articles.

1. GNU Radio: Tools for exploring the radio frequency spectrum;Blossom;Linux J.,2004

2. Random forests;Breiman;Mach. Learn.,2001

3. Screaming channels: when electromagnetic side channels meet radio transceivers;Camurati,2018

4. A $40 software-defined radio;Cass;IEEE Spectrum,2013

5. Application inference using machine learning based side channel analysis;Chawla,2019

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Electromagnetic Signal Analysis: A Vulnerability to Edge Computing Driven IoT Devices;2023 4th International Conference on Computing and Communication Systems (I3CS);2023-03-16

2. Data Exfiltration through Electromagnetic Covert Channel of Wired Industrial Control Systems;Applied Sciences;2023-02-24

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