Preliminary Study of Novel Bio-Crypto Key Generation Using Clustering-Based Binarization of ECG Features
In modern society, the popularity of wearable devices has highlighted the need for data security. Bio-crypto keys (bio-keys), especially in the context of wearable devices, are gaining attention as a next-generation security method. Despite the theoretical advantages of bio-keys, implementing such s...
| Main Authors: | , , , , , |
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| Format: | Article |
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MDPI AG
2024-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/5/1556 |
| _version_ | 1797263884368740352 |
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| author | Ho Bin Hwang Jeyeon Lee Hyeokchan Kwon Byungho Chung Jongshill Lee In Young Kim |
| author_facet | Ho Bin Hwang Jeyeon Lee Hyeokchan Kwon Byungho Chung Jongshill Lee In Young Kim |
| author_sort | Ho Bin Hwang |
| collection | DOAJ |
| description | In modern society, the popularity of wearable devices has highlighted the need for data security. Bio-crypto keys (bio-keys), especially in the context of wearable devices, are gaining attention as a next-generation security method. Despite the theoretical advantages of bio-keys, implementing such systems poses practical challenges due to their need for flexibility and convenience. Electrocardiograms (ECGs) have emerged as a potential solution to these issues but face hurdles due to intra-individual variability. This study aims to evaluate the possibility of a stable, flexible, and convenient-to-use bio-key using ECGs. We propose an approach that minimizes biosignal variability using normalization, clustering-based binarization, and the fuzzy extractor, enabling the generation of personalized seeds and offering ease of use. The proposed method achieved a maximum entropy of 0.99 and an authentication accuracy of 95%. This study evaluated various parameter combinations for generating effective bio-keys for personal authentication and proposed the optimal combination. Our research holds potential for security technologies applicable to wearable devices and healthcare systems. |
| first_indexed | 2024-04-25T00:20:06Z |
| format | Article |
| id | doaj.art-71acf56a98964ae2aa044cad1f1ee2c9 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-25T00:20:06Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-71acf56a98964ae2aa044cad1f1ee2c92024-03-12T16:55:11ZengMDPI AGSensors1424-82202024-02-01245155610.3390/s24051556Preliminary Study of Novel Bio-Crypto Key Generation Using Clustering-Based Binarization of ECG FeaturesHo Bin Hwang0Jeyeon Lee1Hyeokchan Kwon2Byungho Chung3Jongshill Lee4In Young Kim5Department of Biomedical Engineering, Hanyang University, Seoul 04763, Republic of KoreaDepartment of Biomedical Engineering, Hanyang University, Seoul 04763, Republic of KoreaInformation Security Research Division, Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Republic of KoreaInformation Security Research Division, Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Republic of KoreaDepartment of Biomedical Engineering, Hanyang University, Seoul 04763, Republic of KoreaDepartment of Biomedical Engineering, Hanyang University, Seoul 04763, Republic of KoreaIn modern society, the popularity of wearable devices has highlighted the need for data security. Bio-crypto keys (bio-keys), especially in the context of wearable devices, are gaining attention as a next-generation security method. Despite the theoretical advantages of bio-keys, implementing such systems poses practical challenges due to their need for flexibility and convenience. Electrocardiograms (ECGs) have emerged as a potential solution to these issues but face hurdles due to intra-individual variability. This study aims to evaluate the possibility of a stable, flexible, and convenient-to-use bio-key using ECGs. We propose an approach that minimizes biosignal variability using normalization, clustering-based binarization, and the fuzzy extractor, enabling the generation of personalized seeds and offering ease of use. The proposed method achieved a maximum entropy of 0.99 and an authentication accuracy of 95%. This study evaluated various parameter combinations for generating effective bio-keys for personal authentication and proposed the optimal combination. Our research holds potential for security technologies applicable to wearable devices and healthcare systems.https://www.mdpi.com/1424-8220/24/5/1556biometricsECGsignal processingbio-crypto keyauthenticationcryptography |
| spellingShingle | Ho Bin Hwang Jeyeon Lee Hyeokchan Kwon Byungho Chung Jongshill Lee In Young Kim Preliminary Study of Novel Bio-Crypto Key Generation Using Clustering-Based Binarization of ECG Features Sensors biometrics ECG signal processing bio-crypto key authentication cryptography |
| title | Preliminary Study of Novel Bio-Crypto Key Generation Using Clustering-Based Binarization of ECG Features |
| title_full | Preliminary Study of Novel Bio-Crypto Key Generation Using Clustering-Based Binarization of ECG Features |
| title_fullStr | Preliminary Study of Novel Bio-Crypto Key Generation Using Clustering-Based Binarization of ECG Features |
| title_full_unstemmed | Preliminary Study of Novel Bio-Crypto Key Generation Using Clustering-Based Binarization of ECG Features |
| title_short | Preliminary Study of Novel Bio-Crypto Key Generation Using Clustering-Based Binarization of ECG Features |
| title_sort | preliminary study of novel bio crypto key generation using clustering based binarization of ecg features |
| topic | biometrics ECG signal processing bio-crypto key authentication cryptography |
| url | https://www.mdpi.com/1424-8220/24/5/1556 |
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