| Title |
On the design of biometric-based user authentication protocol in smart city environment |
| ID_Doc |
36102 |
| Authors |
Bera, B; Das, AK; Balzano, W; Medaglia, CM |
| Title |
On the design of biometric-based user authentication protocol in smart city environment |
| Year |
2020 |
| Published |
|
| DOI |
10.1016/j.patrec.2020.08.017 |
| Abstract |
Among the security services, like authentication, access control, key management and intrusion detection, user authentication is very much needed for a smart city environment because an external authorized user may require the real time data to be accessed directly from the deployed Internet of Things (IoT) enabled smart devices. Using the established session key between the user and an access smart device though mutual authentication and key agreement process, the real time data can be securely accessed. To deal with this issue, we propose a new user authentication scheme in smart city environment using three factors of a legal registered user (mobile device, password and biometrics). The proposed scheme is shown to be robust against a number of potential attacks needed in an IoT-based smart city deployment. The simulation study for formal security verification using the widely-accepted "Automated Validation of Internet Security Protocols and Applications (AVISPA)" tool demonstrates that the proposed scheme is also secure. Furthermore, experiments on various cryptographic primitives have been carried out using "MIRACL Cryptographic SDK: Multiprecision Integer and Rational Arithmetic Cryptographic Library" under both server and Raspberry PI 3 settings. Finally, a comprehensive comparative analysis shows the effectiveness and better security of the proposed scheme as compared with other state of art user authentication schemes. (C) 2020 Elsevier B.V. All rights reserved. |
| Author Keywords |
Smart city; User authentication; Key agreement; Biometrics; Security; AVISPA; MIRACL |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000579804900059 |
| WoS Category |
Computer Science, Artificial Intelligence |
| Research Area |
Computer Science |
| PDF |
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