An Integrated Secure Efficient Computing Architecture for Embedded and Remote ECG Diagnosis

Bhattarai, Adarsha; Peng, Dongming

doi:10.1007/s42979-022-01465-7

Cited by 4 publications

(1 citation statement)

References 43 publications

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“…A safe and confidential ECG system was proposed [10]. This study merges the FHE method with signal processing via the QRS complex.…”

Section: Related Workmentioning

confidence: 99%

Securing Signal Encryption Based on Reduced Round Homomorphic AES

2023

IJIES

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Cryptography plays a vital role in protecting information that has increased as a result of digitalization. Personal sensitive information, including electrocardiogram (ECG) signals, is widely transferred around the world, and as a result, protecting the data from unauthorized access by attackers is critical. One of the algorithms that is frequently used is the advanced encryption standard (AES) algorithm, due to its remarkable reliability and its usage in a wide range of applications. However, key exchange is still necessary to execute computations on the encrypted data, whereas time is considered the essence of the efficiency of the encryption algorithm. This study proposes and investigates the use of the proposed improved reduced round AES algorithm in conjunction with the new proposed fully homomorphic encryption (FHE) in order to preserve data privacy and eliminate key exchange restrictions. This research was employed to process, encrypt, and decrypt digital ECG signals. The suggested algorithm improves the security level and encryption and decryption times by using fewer rounds of encryption. In order to achieve this goal, it was suggested that the evaluation process be added to the AES algorithm as an extra level of security. With the evaluation process, it is possible to execute a number of computation operations homomorphically on the encrypted data without decrypting it. Additionally, the number of rounds in the AES encryption was decreased from 10 to 5. Results indicate that the proposed algorithm would take 5.39475 × 10 32 years to break, making it more efficient than the traditional AES and others. Also, the proposed algorithm has a classification sensitivity of 95.83% while simultaneously displaying an accuracy of 100%. Additionally, it may be utilized for real-time internet of things (IoT) applications.

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“…A safe and confidential ECG system was proposed [10]. This study merges the FHE method with signal processing via the QRS complex.…”

Section: Related Workmentioning

confidence: 99%