Spoofing detection on adaptive authentication System‐A survey
Abstract With the widespread of computing and mobile devices, authentication using biometrics has received greater attention. Although biometric systems usually provide efficient solutions, the recognition performance tends to be affected over time due to changing conditions and the ageing of biomet...
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| Format: | Article |
| Language: | English |
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Wiley
2022-03-01
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| Series: | IET Biometrics |
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| Online Access: | https://doi.org/10.1049/bme2.12060 |
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| author | Hind Baaqeel Sunday Olusanya Olatunji |
| author_facet | Hind Baaqeel Sunday Olusanya Olatunji |
| author_sort | Hind Baaqeel |
| collection | DOAJ |
| description | Abstract With the widespread of computing and mobile devices, authentication using biometrics has received greater attention. Although biometric systems usually provide efficient solutions, the recognition performance tends to be affected over time due to changing conditions and the ageing of biometric data, which results in intra‐class variability. This issue is one of the leading causes of the high false rejection rate in biometric authentication systems. Fortunately, this issue has been addressed by using adaptive biometric solutions in which the system gradually adapts to new changes in user biometrics. However, their adaptability to changes may be exploited by an attacker to compromise the stored templates, either to impersonate a specific client or to deny access to him/her. In this work, the authors will carry out a systematic literature review by conducting a comparative study on state‐of‐the‐art solutions for spoofing detection on adaptive authentication systems. This paper will identify the main issues that need to be addressed in adaptive authentication systems. Thus, the authors aim to encourage researchers to develop more robust adaptive solutions to overcome the identified gaps in this research. |
| format | Article |
| id | doaj-art-0bc7212940b24ad3829bc52ce973c71d |
| institution | Kabale University |
| issn | 2047-4938 2047-4946 |
| language | English |
| publishDate | 2022-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Biometrics |
| spelling | doaj-art-0bc7212940b24ad3829bc52ce973c71d2025-02-03T01:29:37ZengWileyIET Biometrics2047-49382047-49462022-03-01112879610.1049/bme2.12060Spoofing detection on adaptive authentication System‐A surveyHind Baaqeel0Sunday Olusanya Olatunji1Computer Science Department College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University Dammam Saudi ArabiaSAUDI ARAMCO Cybersecurity Chair College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University Dammam Saudi ArabiaAbstract With the widespread of computing and mobile devices, authentication using biometrics has received greater attention. Although biometric systems usually provide efficient solutions, the recognition performance tends to be affected over time due to changing conditions and the ageing of biometric data, which results in intra‐class variability. This issue is one of the leading causes of the high false rejection rate in biometric authentication systems. Fortunately, this issue has been addressed by using adaptive biometric solutions in which the system gradually adapts to new changes in user biometrics. However, their adaptability to changes may be exploited by an attacker to compromise the stored templates, either to impersonate a specific client or to deny access to him/her. In this work, the authors will carry out a systematic literature review by conducting a comparative study on state‐of‐the‐art solutions for spoofing detection on adaptive authentication systems. This paper will identify the main issues that need to be addressed in adaptive authentication systems. Thus, the authors aim to encourage researchers to develop more robust adaptive solutions to overcome the identified gaps in this research.https://doi.org/10.1049/bme2.12060adaptive authenticationbiometricssecurity and privacyuser authentication |
| spellingShingle | Hind Baaqeel Sunday Olusanya Olatunji Spoofing detection on adaptive authentication System‐A survey IET Biometrics adaptive authentication biometrics security and privacy user authentication |
| title | Spoofing detection on adaptive authentication System‐A survey |
| title_full | Spoofing detection on adaptive authentication System‐A survey |
| title_fullStr | Spoofing detection on adaptive authentication System‐A survey |
| title_full_unstemmed | Spoofing detection on adaptive authentication System‐A survey |
| title_short | Spoofing detection on adaptive authentication System‐A survey |
| title_sort | spoofing detection on adaptive authentication system a survey |
| topic | adaptive authentication biometrics security and privacy user authentication |
| url | https://doi.org/10.1049/bme2.12060 |
| work_keys_str_mv | AT hindbaaqeel spoofingdetectiononadaptiveauthenticationsystemasurvey AT sundayolusanyaolatunji spoofingdetectiononadaptiveauthenticationsystemasurvey |