ThingNet: A Lightweight Real-time Mirai IoT Variants Hunter through CPU Power Fingerprinting-Reference-Cited by-同舟云学术

ThingNet: A Lightweight Real-time Mirai IoT Variants Hunter through CPU Power Fingerprinting

Published:2022-03-14 Issue: Volume: Page:
ISSN:
Container-title:2022 Design, Automation & Test in Europe Conference & Exhibition (DATE)
language:
Short-container-title:

Author:

Li Zhuoran¹,Zhao Dan¹

Affiliation:

1. Department of Computer Science, Old Dominion University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9774496/9774497/09774536.pdf?arnumber=9774536

Reference25 articles.

1. MTHAEL: Cross-Architecture IoT Malware Detection Based on Neural Network Advanced Ensemble Learning

2. Air-viber: Exfiltrating data from air-gapped computers via covert surface vibrations;guri;CoRR,2020

3. Detecting anomalous programmable logic controller behavior using RF-based Hilbert transform features and a correlation-based verification process

4. Wattsupdoc: Power side channels to nonintrusively discover untargeted malware on embedded medical devices;clark;2013 USENIX Workshop on Health Information Technologies (HealthTech 13),2013

5. Mobile Malware Detection Based on Energy Fingerprints — A Dead End?

Cited by 3 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. DeepIncept: Diversify Performance Counters with Deep Learning to Detect Malware;2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC);2024-01-22

2. μThingNet: Leveraging Fine-Grained Power Analysis towards A Robust Zero-Day Defender;2023 IEEE 36th International System-on-Chip Conference (SOCC);2023-09-05

3. Enimanal: Augmented cross-architecture IoT malware analysis using graph neural networks;Computers & Security;2023-09