An Innovative Honeypot Architecture for Detecting and Mitigating Hardware Trojans in IoT Devices

The exponential growth and widespread adoption of Internet of Things (IoT) devices have introduced many vulnerabilities. Attackers frequently exploit these flaws, necessitating advanced technological approaches to protect against emerging cyber threats. This paper introduces a novel approach utilizing hardware honeypots as an additional defensive layer against hardware vulnerabilities, particularly hardware Trojans (HTs). HTs pose significant risks to the security of modern integrated circuits (ICs), potentially causing operational failures, denial of service, or data leakage through intentional modifications. The proposed system was implemented on a Raspberry Pi and tested on an emulated HT circuit using a Field-Programmable Gate Array (FPGA). This approach leverages hardware honeypots to detect and mitigate HTs in the IoT devices. The results demonstrate that the system effectively detects and mitigates HTs without imposing additional complexity on the IoT devices. The Trojan-agnostic solution offers full customization to meet specific security needs, providing a flexible and robust layer of security. These findings provide valuable insights into enhancing the security of IoT devices against hardware-based cyber threats, thereby contributing to the overall resilience of IoT networks. This innovative approach offers a promising solution to address the growing security challenges in IoT environments.

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Publication Details

Journal
IoT
Published
2024-10-31
DOI
https://doi.org/10.3390/iot5040033
Citations
11
Primary Topic
Physical Unclonable Functions (PUFs) and Hardware Security
Type
article
Field-Weighted Citation Impact
5.38
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article

An Innovative Honeypot Architecture for Detecting and Mitigating Hardware Trojans in IoT Devices

Donatien Koulla Moulla, Alain Abran, Hassan Soubra, Abdul Halim Omar
11 citations
IoT
Physical Unclonable Functions (PUFs) and Hardware Security
5.38
article

An Innovative Honeypot Architecture for Detecting and Mitigating Hardware Trojans in IoT Devices

Donatien Koulla Moulla, Alain Abran, Hassan Soubra, Abdul Halim Omar
article en
11 citations

Abstract

The exponential growth and widespread adoption of Internet of Things (IoT) devices have introduced many vulnerabilities. Attackers frequently exploit these flaws, necessitating advanced technological approaches to protect against emerging cyber threats. This paper introduces a novel approach utilizing hardware honeypots as an additional defensive layer against hardware vulnerabilities, particularly hardware Trojans (HTs). HTs pose significant risks to the security of modern integrated circuits (ICs), potentially causing operational failures, denial of service, or data leakage through intentional modifications. The proposed system was implemented on a Raspberry Pi and tested on an emulated HT circuit using a Field-Programmable Gate Array (FPGA). This approach leverages hardware honeypots to detect and mitigate HTs in the IoT devices. The results demonstrate that the system effectively detects and mitigates HTs without imposing additional complexity on the IoT devices. The Trojan-agnostic solution offers full customization to meet specific security needs, providing a flexible and robust layer of security. These findings provide valuable insights into enhancing the security of IoT devices against hardware-based cyber threats, thereby contributing to the overall resilience of IoT networks. This innovative approach offers a promising solution to address the growing security challenges in IoT environments.

IoTVol. 5(4)
École Centrale de Lyon (FR), University of South Africa (ZA), École Centrale d'Électronique (FR), German University in Cairo (EG), École de Technologie Supérieure (CA)
Openalex Percentile: Top 3%
Physical Unclonable Functions (PUFs) and Hardware Security
5.38
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An Innovative Honeypot Architecture for Detecting and Mitigating Hardware Trojans in IoT Devices — Donatien Koulla Moulla, Alain Abran, et al. · IoT (2024) | TGRS Research Map | TGRS