Patterns-of-Life Aided Authentication
Wireless Body Area Network (WBAN) applications have grown immensely in the past few years. However, security and privacy of the user are two major obstacles in their development. The complex and very sensitive nature of the body-mounted sensors means the traditional network layer security arrangemen...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-09-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/16/10/1574 |
| _version_ | 1818001818221805568 |
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| author | Nan Zhao Aifeng Ren Zhiya Zhang Tianqiao Zhu Masood Ur Rehman Xiaodong Yang Fangming Hu |
| author_facet | Nan Zhao Aifeng Ren Zhiya Zhang Tianqiao Zhu Masood Ur Rehman Xiaodong Yang Fangming Hu |
| author_sort | Nan Zhao |
| collection | DOAJ |
| description | Wireless Body Area Network (WBAN) applications have grown immensely in the past few years. However, security and privacy of the user are two major obstacles in their development. The complex and very sensitive nature of the body-mounted sensors means the traditional network layer security arrangements are not sufficient to employ their full potential, and novel solutions are necessary. In contrast, security methods based on physical layers tend to be more suitable and have simple requirements. The problem of initial trust needs to be addressed as a prelude to the physical layer security key arrangement. This paper proposes a patterns-of-life aided authentication model to solve this issue. The model employs the wireless channel fingerprint created by the user’s behavior characterization. The performance of the proposed model is established through experimental measurements at 2.45 GHz. Experimental results show that high correlation values of 0.852 to 0.959 with the habitual action of the user in different scenarios can be used for auxiliary identity authentication, which is a scalable result for future studies. |
| first_indexed | 2024-04-14T03:38:13Z |
| format | Article |
| id | doaj.art-fa2c6471f554481588c97e394b8613fb |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T03:38:13Z |
| publishDate | 2016-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-fa2c6471f554481588c97e394b8613fb2022-12-22T02:14:39ZengMDPI AGSensors1424-82202016-09-011610157410.3390/s16101574s16101574Patterns-of-Life Aided AuthenticationNan Zhao0Aifeng Ren1Zhiya Zhang2Tianqiao Zhu3Masood Ur Rehman4Xiaodong Yang5Fangming Hu6School of Electronic Engineering, Xidian University, Xi’an 710071, ChinaSchool of Electronic Engineering, Xidian University, Xi’an 710071, ChinaSchool of Electronic Engineering, Xidian University, Xi’an 710071, ChinaSchool of Electronic Engineering, Xidian University, Xi’an 710071, ChinaCentre for Wireless Research, University of Bedfordshire, Luton LU1 3JU, UKSchool of Electronic Engineering, Xidian University, Xi’an 710071, ChinaSchool of Electronic Engineering, Xidian University, Xi’an 710071, ChinaWireless Body Area Network (WBAN) applications have grown immensely in the past few years. However, security and privacy of the user are two major obstacles in their development. The complex and very sensitive nature of the body-mounted sensors means the traditional network layer security arrangements are not sufficient to employ their full potential, and novel solutions are necessary. In contrast, security methods based on physical layers tend to be more suitable and have simple requirements. The problem of initial trust needs to be addressed as a prelude to the physical layer security key arrangement. This paper proposes a patterns-of-life aided authentication model to solve this issue. The model employs the wireless channel fingerprint created by the user’s behavior characterization. The performance of the proposed model is established through experimental measurements at 2.45 GHz. Experimental results show that high correlation values of 0.852 to 0.959 with the habitual action of the user in different scenarios can be used for auxiliary identity authentication, which is a scalable result for future studies.http://www.mdpi.com/1424-8220/16/10/1574Wireless Body Area Networksinitial trustpatterns-of-life aided authentication |
| spellingShingle | Nan Zhao Aifeng Ren Zhiya Zhang Tianqiao Zhu Masood Ur Rehman Xiaodong Yang Fangming Hu Patterns-of-Life Aided Authentication Sensors Wireless Body Area Networks initial trust patterns-of-life aided authentication |
| title | Patterns-of-Life Aided Authentication |
| title_full | Patterns-of-Life Aided Authentication |
| title_fullStr | Patterns-of-Life Aided Authentication |
| title_full_unstemmed | Patterns-of-Life Aided Authentication |
| title_short | Patterns-of-Life Aided Authentication |
| title_sort | patterns of life aided authentication |
| topic | Wireless Body Area Networks initial trust patterns-of-life aided authentication |
| url | http://www.mdpi.com/1424-8220/16/10/1574 |
| work_keys_str_mv | AT nanzhao patternsoflifeaidedauthentication AT aifengren patternsoflifeaidedauthentication AT zhiyazhang patternsoflifeaidedauthentication AT tianqiaozhu patternsoflifeaidedauthentication AT masoodurrehman patternsoflifeaidedauthentication AT xiaodongyang patternsoflifeaidedauthentication AT fangminghu patternsoflifeaidedauthentication |