A Cryptographic Security Engine With Sequence Tracker for Implantable Neural Stimulation Devices

Neural stimulation devices have shown a significant impact on the treatment of neurological disorders such as Parkinson’s disease, epilepsy, and chronic pain. Maintaining secure communication with these devices is essential to keep the confidentiality and integrity of the patient’s data and the authenticity of the transmitter. The proposed work provides a framework for a power-aware security engine for such implantable devices by incorporating a cryptographic security engine to ensure the message’s confidentiality, integrity, and authenticity. While prior works focus on confidentiality, the proposed engine involves the use of AES-128 decryption and a sequence tracker to ensure confidentiality, integrity, and authenticity by disabling malicious repeat attacks to realize secure implantable neural stimulators. The security engine is tested and functionally verified on an FPGA and implemented in a CMOS 65 nm process, resulting in a $0.09 \mathrm{~mm}^{2}$ area and $45 \mu \mathrm{~W}$ power consumption.

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Publication Details

Published
2024-10-24
DOI
https://doi.org/10.1109/biocas61083.2024.10798193
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
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article

A Cryptographic Security Engine With Sequence Tracker for Implantable Neural Stimulation Devices

Anshul Garg, Saravanan Vijayakumaran, Laxmeesha Somappa, Tejas Amritkar
Neuroscience and Neural Engineering
article

A Cryptographic Security Engine With Sequence Tracker for Implantable Neural Stimulation Devices

Anshul Garg, Saravanan Vijayakumaran, Laxmeesha Somappa, Tejas Amritkar
article en

Abstract

Neural stimulation devices have shown a significant impact on the treatment of neurological disorders such as Parkinson’s disease, epilepsy, and chronic pain. Maintaining secure communication with these devices is essential to keep the confidentiality and integrity of the patient’s data and the authenticity of the transmitter. The proposed work provides a framework for a power-aware security engine for such implantable devices by incorporating a cryptographic security engine to ensure the message’s confidentiality, integrity, and authenticity. While prior works focus on confidentiality, the proposed engine involves the use of AES-128 decryption and a sequence tracker to ensure confidentiality, integrity, and authenticity by disabling malicious repeat attacks to realize secure implantable neural stimulators. The security engine is tested and functionally verified on an FPGA and implemented in a CMOS 65 nm process, resulting in a $0.09 \mathrm{~mm}^{2}$ area and $45 \mu \mathrm{~W}$ power consumption.

Indian Institute of Technology Bombay (IN)
Openalex Percentile: Top 74%
Neuroscience and Neural Engineering
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