MADEA: A Malware Detection Architecture for IoT Blending Network Monitoring and Device Attestation
Internet-of-Things (IoT) devices are vulnerable to malware and require new mitigation techniques due to their limited resources. To that end, previous research has used periodic Remote Attestation (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R A$</tex>) or Traffic Analysis (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathcal{T} A$</tex>) to detect malware in IoT devices. However, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathcal{R A}$</tex> is expensive, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathcal{T}$</tex> A only raises suspicion without confirming malware presence. To solve this, we design MADEA, the first system that blends <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathcal{R A}$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathcal{T A}$</tex> to offer a comprehensive approach to malware detection for IoT. <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathcal{T}$</tex> A builds profiles of expected packet traces during benign operations of each device and then uses them to detect malware from network traffic in real-time. <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathcal{R A}$</tex> confirms the presence or absence of malware on the device. MADEA achieves 100 % true positive rate. It also outperforms other approaches with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$160 \times$</tex> faster detection time. Finally, without MADEA, effective periodic <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathcal{R A}$</tex> can consume at least <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\sim 14 \times$</tex> the amount of energy that a device needs in one hour.
Authors
- Gene Tsudik (ORCID: https://orcid.org/0000-0002-8467-8614)
- Athina Markopoulou (ORCID: https://orcid.org/0000-0003-1803-8675)
- Renascence Tarafder Prapty
- Sashidhar Jakkamsetti (ORCID: https://orcid.org/0000-0002-5338-3522)
- Rahmadi Trimananda (ORCID: https://orcid.org/0000-0002-9900-7506)
Institutions
- University of California, Irvine (US)
- UC Irvine Health (US)
- Irvine University (US)
- Robert Bosch (Germany) (DE)
Publication Details
- Published
- 2025-06-08
- DOI
- https://doi.org/10.1109/icc52391.2025.11161770
- Primary Topic
- Advanced Malware Detection Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00