LiteCrypt: Enhancing IoMT Security with Optimized HE and Lightweight Dual-Authorization

The integration of 5G/6G networks with intelligent healthcare systems has enabled early disease detection through patient data monitoring. However, the Internet of Medical Things (IoMT) and remote healthcare services introduce significant privacy and security risks. In this paper, we propose LiteCry...

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Published in:Proceedings - International Conference on Parallel and Distributed Systems pp. 166 - 175
Main Authors: Xie, Qipeng, Wang, Weizheng, Huang, Yongzhi, Zheng, Mengyao, Shang, Shuai, Jiang, Linshan, Khan, Salabat, Wu, Kaishun
Format: Conference Proceeding
Language:English
Published: IEEE 10.10.2024
Subjects:
Cryptography
GPU Acceleration
Homomorphic encryption
Machine Learning
Memory management
Monitoring
Performance evaluation
Performance gain
Privacy
Protocols
Real-time systems
Telemedicine
Threshold Signature
ISSN:2690-5965
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Abstract The integration of 5G/6G networks with intelligent healthcare systems has enabled early disease detection through patient data monitoring. However, the Internet of Medical Things (IoMT) and remote healthcare services introduce significant privacy and security risks. In this paper, we propose LiteCrypt, which addresses these challenges by introducing an optimized Homomorphic Convolutional Neural Networks (HCNN) structure for secure inference and a lightweight Threshold Signature Scheme (TSS) based dual-authorization mechanism. To enhance the practicality of Homomorphic Encryption (HE)-based secure inference in telemedicine applications, LiteCrypt presents an optimized HCNN framework that ensures efficient and adaptable operations across multiple datasets. A high-performance GPU-accelerated HE engine is developed to address the computational demands of HE operations, enabling real-time processing of encrypted patient data. Besides, LiteCrypt introduces a novel TSS-based dual-authorization protocol, requiring consent from both the patient and the hospital to access patient data, thereby mitigating unauthorized access risks. The system adapts to a flexible 2-out-of-3 authorization scheme for emergencies, ensuring timely data retrieval while maintaining security. To overcome the initial challenge of prolonged computation time due to compute-intensive operations, In LiteCrypt, we utilized the lightweight TSS protocol, based on Oblivious Transfer (OT), which is designed for resource-constrained IoMT devices, reducing computation time from 11.9 to 0.11 seconds. Empirical validation demonstrates LiteCrypt's superior performance, achieving a 233-fold increase in processing speed, a 96 \% reduction in encrypted message size, and a 28-fold speed increase using GPUs.
AbstractList The integration of 5G/6G networks with intelligent healthcare systems has enabled early disease detection through patient data monitoring. However, the Internet of Medical Things (IoMT) and remote healthcare services introduce significant privacy and security risks. In this paper, we propose LiteCrypt, which addresses these challenges by introducing an optimized Homomorphic Convolutional Neural Networks (HCNN) structure for secure inference and a lightweight Threshold Signature Scheme (TSS) based dual-authorization mechanism. To enhance the practicality of Homomorphic Encryption (HE)-based secure inference in telemedicine applications, LiteCrypt presents an optimized HCNN framework that ensures efficient and adaptable operations across multiple datasets. A high-performance GPU-accelerated HE engine is developed to address the computational demands of HE operations, enabling real-time processing of encrypted patient data. Besides, LiteCrypt introduces a novel TSS-based dual-authorization protocol, requiring consent from both the patient and the hospital to access patient data, thereby mitigating unauthorized access risks. The system adapts to a flexible 2-out-of-3 authorization scheme for emergencies, ensuring timely data retrieval while maintaining security. To overcome the initial challenge of prolonged computation time due to compute-intensive operations, In LiteCrypt, we utilized the lightweight TSS protocol, based on Oblivious Transfer (OT), which is designed for resource-constrained IoMT devices, reducing computation time from 11.9 to 0.11 seconds. Empirical validation demonstrates LiteCrypt's superior performance, achieving a 233-fold increase in processing speed, a 96 \% reduction in encrypted message size, and a 28-fold speed increase using GPUs.
Author Xie, Qipeng
Khan, Salabat
Huang, Yongzhi
Wu, Kaishun
Wang, Weizheng
Zheng, Mengyao
Shang, Shuai
Jiang, Linshan
Author_xml – sequence: 1
  givenname: Qipeng
  surname: Xie
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  organization: Hong Kong University of Science and Technology (Guang Zhou),IoT Thrust,Guang Zhou,China
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  givenname: Weizheng
  surname: Wang
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  organization: Hong Kong University of Science and Technology (Guang Zhou),IoT Thrust,Guang Zhou,China
– sequence: 8
  givenname: Kaishun
  surname: Wu
  fullname: Wu, Kaishun
  organization: Hong Kong University of Science and Technology (Guang Zhou),IoT Thrust,Guang Zhou,China
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Snippet The integration of 5G/6G networks with intelligent healthcare systems has enabled early disease detection through patient data monitoring. However, the...
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StartPage 166
SubjectTerms Cryptography
GPU Acceleration
Homomorphic encryption
Machine Learning
Memory management
Monitoring
Performance evaluation
Performance gain
Privacy
Protocols
Real-time systems
Telemedicine
Threshold Signature
Title LiteCrypt: Enhancing IoMT Security with Optimized HE and Lightweight Dual-Authorization
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