An efficient method for Secure ECG Feature Based Cryptographic Key Generation

Premkumar*, S.; Mohana, J.

doi:10.35940/ijitee.l3506.1081219

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…There are several data encryption and cryptography approaches available for data security that can safeguard data even for those without an encryption method. However, there are still certain restrictions on data storage and database retrieval (Premkumar and Mohana. 2020).…”

Section: Proposed Workmentioning

confidence: 99%

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Bilateral Hashing model of ECG signal encryption system using Downhill Peak Follow (DPF) based Encryption technique

2023

Preprint

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This research suggests a unique ECG security solution based on the data pattern-based encryption paradigm to address security issues in ECG signal transmission or storage environments. According to this concept, the encryption system controls the data security process by extracting key signatures from the ECG signal peaks to identify the characteristics or attributes of the data and encrypt it. To estimate the hashing qualities, the approach is to build a random key pattern based on the signal peaks and extract the signature. The signal was then encrypted and sent to a doctor or signal analyzer. The Bilateral Random Hashing (BRH) is used to achieve this. This updates the hashing generation model by analyzing the parameters using probabilistic distributional characteristics. This crucial motif was applied. This key pattern was utilized to encrypt the data samples using the Downhill Peak Follow (DPF) encryption technique, which follows the strength of the peak value in the ECG waveform. This suggested project is carried out using MATLAB scripting.

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Section: Proposed Workmentioning

confidence: 99%

“…The hashing techniques are used as in the earlier Premkumar and Mohana (2020), to secure the data with high sensitive structure. These methods are to generate the random key for the private key model to provide unique key formation.…”

Section: Estimate the Width Of The Ecg Signal 'W' Based On The Freque...mentioning

confidence: 99%

Bilateral Hashing model of ECG signal encryption system using Downhill Peak Follow (DPF) based Encryption technique

2023

Preprint

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Fused Multi-Domains and Adaptive Variational Mode Decomposition ECG Feature Extraction for Lightweight Bio-Inspired Key Generation and Encryption

Agbehadji,

Millham,

Freeman

et al. 2024

Sensors

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Security is one of the increasingly significant issues given advancements in technology that harness data from multiple devices such as the internet of medical devices. While protecting data from unauthorized user access, several techniques are used including fingerprints, passwords, and others. One of the techniques that has attracted much attention is the use of human features, which has proven to be most effective because of the difficulties in impersonating human-related features. An example of a human-related attribute includes the electrical signal generated from the heart, mostly referred to as an Electrocardiogram (ECG) signal. The methods to extract features from ECG signals are time domain-based; however, the challenge with relying only on the time-domain or frequency-domain method is the inability to capture the intra-leading relationship of Variational Mode Decomposition signals. In this research, fusing multiple domains ECG feature and adaptive Variational Mode Decomposition approaches are utilized to mitigate the challenge of losing the intra-leading correlations of mode decompositions, which might reduce the robustness of encryption algorithms. The features extracted using the reconstructed signal have a mean (0.0004), standard deviation (0.0391), skewness (0.1562), and kurtosis (1.2205). Among the lightweight encryption methods considered, Chacha20 has a total execution time of 27µs. The study proposes a lightweight encryption technique based on the fused vector representation of extracted features to provide an encryption scheme in addition to a bio-inspired key generation technique for data encryption.

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An efficient method for Secure ECG Feature Based Cryptographic Key Generation

Cited by 2 publications

References 2 publications

Bilateral Hashing model of ECG signal encryption system using Downhill Peak Follow (DPF) based Encryption technique

Bilateral Hashing model of ECG signal encryption system using Downhill Peak Follow (DPF) based Encryption technique

Fused Multi-Domains and Adaptive Variational Mode Decomposition ECG Feature Extraction for Lightweight Bio-Inspired Key Generation and Encryption

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