TY - GEN
T1 - Securing Fault Diagnosis in IoT-Enabled Industrial Systems Using Homomorphic Encryption
AU - El-Hajj, Mohammed
AU - El Attar, Ali
AU - Fadllallah, Ahmad
AU - Khatoun, Rida
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025/1/1
Y1 - 2025/1/1
N2 - Securing fault diagnosis in IoT-enabled industrial systems is critical to preventing data breaches and ensuring reliable operation. This study proposes a novel approach that integrates homomorphic encryption (HE) into the fault diagnosis pipeline, enabling secure processing of sensitive sensor data. Using the CWRU Bearing Dataset, we demonstrate that the HE-based system achieves high accuracy (97.92%) while preserving data confidentiality. Despite the computational overhead introducing latency (1100 ms), the trade-off remains acceptable for non-real-time applications. The system’s ability to protect privacy without significantly compromising performance makes it well-suited for sensitive industries such as healthcare and manufacturing. Future work includes optimizing HE algorithms and exploring hybrid encryption schemes to enhance scalability and efficiency. This research highlights HE as a promising solution for secure and effective fault diagnosis in IoT systems.
AB - Securing fault diagnosis in IoT-enabled industrial systems is critical to preventing data breaches and ensuring reliable operation. This study proposes a novel approach that integrates homomorphic encryption (HE) into the fault diagnosis pipeline, enabling secure processing of sensitive sensor data. Using the CWRU Bearing Dataset, we demonstrate that the HE-based system achieves high accuracy (97.92%) while preserving data confidentiality. Despite the computational overhead introducing latency (1100 ms), the trade-off remains acceptable for non-real-time applications. The system’s ability to protect privacy without significantly compromising performance makes it well-suited for sensitive industries such as healthcare and manufacturing. Future work includes optimizing HE algorithms and exploring hybrid encryption schemes to enhance scalability and efficiency. This research highlights HE as a promising solution for secure and effective fault diagnosis in IoT systems.
KW - Fault Diagnosis
KW - Homomorphic Encryption (HE)
KW - Industrial IoT (IIoT)
KW - IoT Security
KW - Privacy-Preserving Computation
UR - https://www.scopus.com/pages/publications/105012573274
U2 - 10.1109/NTMS65597.2025.11076966
DO - 10.1109/NTMS65597.2025.11076966
M3 - Conference contribution
AN - SCOPUS:105012573274
T3 - 2025 12th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2025
SP - 280
EP - 287
BT - 2025 12th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2025
Y2 - 18 June 2025 through 20 June 2025
ER -