A High-Throughput Random Binary Sequence Generator Based on ECG
A Wireless Body Area Network (WBAN) is a network that expands over the human body, consisting of multiple nodes that are connected through wireless channels. It offers many applications in the area of remote health care. Maintaining the security of health information in WBAN is an essential requirem...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9802106/ |
| _version_ | 1811327706673971200 |
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| author | Christine Zenieh Mohamed Mazen Al-Mahairi Moufid Haddad |
| author_facet | Christine Zenieh Mohamed Mazen Al-Mahairi Moufid Haddad |
| author_sort | Christine Zenieh |
| collection | DOAJ |
| description | A Wireless Body Area Network (WBAN) is a network that expands over the human body, consisting of multiple nodes that are connected through wireless channels. It offers many applications in the area of remote health care. Maintaining the security of health information in WBAN is an essential requirement. One aspect of ensuring WBAN security is the generation of random binary sequences (RBSs), e.g., encryption keys generation. Due to the very limited resources of WBAN sensors, traditional pseudorandom number generators cannot be used. To reduce resource consumption, some researchers suggested using biometrics in generating RBSs, specifically the electrocardiogram (ECG) signal. However, their methods suffer from low throughput, so they are not suitable for real-time healthcare applications. In this paper, we present a new random sequence generator based on the ECG signal. Our contribution is to build a random sequence generator that generates different length RBSs and has throughput tens or hundreds of times higher than previous methods. Our generator reduces resource consumption due to its very simple processing operations. To evaluate the proposed generator, RBSs of different lengths (128, 256, 512, 1024, 2048 bits) were generated from two ECG datasets, the first is for healthy people, and the second is for people who suffer from arrhythmia. The randomness and distinctiveness of the generated RBSs are evaluated using the National Institute of Standards and Technology (NIST) statistical tests and the Hamming distance. Thus, we have proved that the resulting RBSs are appropriate for information security applications. |
| first_indexed | 2024-04-13T15:11:44Z |
| format | Article |
| id | doaj.art-e95ad334a5c34843a2ce0838ec8308cc |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-13T15:11:44Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e95ad334a5c34843a2ce0838ec8308cc2022-12-22T02:41:59ZengIEEEIEEE Access2169-35362022-01-0110671176712710.1109/ACCESS.2022.31850579802106A High-Throughput Random Binary Sequence Generator Based on ECGChristine Zenieh0https://orcid.org/0000-0002-1107-4190Mohamed Mazen Al-Mahairi1Moufid Haddad2Computer and Automation Engineering Department, Faculty of Mechanical and Electrical Engineering, Damascus University, Damascus, SyriaComputer and Automation Engineering Department, Faculty of Mechanical and Electrical Engineering, Damascus University, Damascus, SyriaComputer and Automation Engineering Department, Faculty of Mechanical and Electrical Engineering, Damascus University, Damascus, SyriaA Wireless Body Area Network (WBAN) is a network that expands over the human body, consisting of multiple nodes that are connected through wireless channels. It offers many applications in the area of remote health care. Maintaining the security of health information in WBAN is an essential requirement. One aspect of ensuring WBAN security is the generation of random binary sequences (RBSs), e.g., encryption keys generation. Due to the very limited resources of WBAN sensors, traditional pseudorandom number generators cannot be used. To reduce resource consumption, some researchers suggested using biometrics in generating RBSs, specifically the electrocardiogram (ECG) signal. However, their methods suffer from low throughput, so they are not suitable for real-time healthcare applications. In this paper, we present a new random sequence generator based on the ECG signal. Our contribution is to build a random sequence generator that generates different length RBSs and has throughput tens or hundreds of times higher than previous methods. Our generator reduces resource consumption due to its very simple processing operations. To evaluate the proposed generator, RBSs of different lengths (128, 256, 512, 1024, 2048 bits) were generated from two ECG datasets, the first is for healthy people, and the second is for people who suffer from arrhythmia. The randomness and distinctiveness of the generated RBSs are evaluated using the National Institute of Standards and Technology (NIST) statistical tests and the Hamming distance. Thus, we have proved that the resulting RBSs are appropriate for information security applications.https://ieeexplore.ieee.org/document/9802106/Electrocardiogrampseudorandom number generatorrandom bit sequencerandom number generatorwireless body area network |
| spellingShingle | Christine Zenieh Mohamed Mazen Al-Mahairi Moufid Haddad A High-Throughput Random Binary Sequence Generator Based on ECG IEEE Access Electrocardiogram pseudorandom number generator random bit sequence random number generator wireless body area network |
| title | A High-Throughput Random Binary Sequence Generator Based on ECG |
| title_full | A High-Throughput Random Binary Sequence Generator Based on ECG |
| title_fullStr | A High-Throughput Random Binary Sequence Generator Based on ECG |
| title_full_unstemmed | A High-Throughput Random Binary Sequence Generator Based on ECG |
| title_short | A High-Throughput Random Binary Sequence Generator Based on ECG |
| title_sort | high throughput random binary sequence generator based on ecg |
| topic | Electrocardiogram pseudorandom number generator random bit sequence random number generator wireless body area network |
| url | https://ieeexplore.ieee.org/document/9802106/ |
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