Smart Cards with Biometric Influences: An Enhanced ID Authentication

Management of flow of all kinds of objects including human beings signifies their real time monitoring. This paper outlines the advantages accrued out of biometrics integration with Smartcards. It showcases the identity authentication employed through different biometric techniques. Biometric key considerations influencing the essence of this technology in Smartcards have been discussed briefly in this paper. With better accuracy and highly reliable support system this technology finds itself today in widespread deployment. However, there are still some concerns with human interfaces along with important factors in implementations of biometrics with smartcards which have been highlighted in this article. This paper also examines the privacy concerns of users in addressing their apprehensions to protect their confidentiality through biometric encryption and proposes DNA technology as a best possible biometric solution. However, due to inherent limitations of its processing time and an instant requirement of authentication, it has been suggested in the proposed modal to use it with combination of one or more suitable biometric technologies. An instant access has been proposed to the user with limited rights by using biometric technology other than the DNA as a primary source of authentication. DNA has been proposed as secondary source of authentication where only after due sample comparison full access rights to the user will be granted. This paper also aims in highlighting the number of advantages offered by the integration of biometrics with smartcards. It also discusses the need to tackle existing challenges due to restrictions in processing of different biometric technologies by defining certain specific future scopes for improvements in existing biometric technologies mainly against the time taken by it for sample comparisons.

[1]  Min-Shiang Hwang,et al.  Cryptanalysis of the Mutual Authentication and Key Agreement Protocol with Smart Cards for Wireless Communications , 2019, Int. J. Netw. Secur..

[2]  Yunpeng Wang,et al.  Understanding commuting patterns using transit smart card data , 2017 .

[3]  Dazhi Sun,et al.  Smart Card Data Mining of Public Transport Destination: A Literature Review , 2018, Inf..

[4]  Jufu Feng,et al.  High-Resolution Mobile Fingerprint Matching via Deep Joint KNN-Triplet Embedding , 2017, AAAI.

[5]  Prakash Annamalai,et al.  Soft Biometrics Traits for Continuous Authentication in Online Exam Using ICA Based Facial Recognition , 2018, Int. J. Netw. Secur..

[6]  Alawi A. Al-saggaf Key binding biometrics-based remote user authentication scheme using smart cards , 2017, IET Biom..

[7]  Fadi Al-Turjman,et al.  Confidential smart-sensing framework in the IoT era , 2018, The Journal of Supercomputing.

[8]  Yen-Lung Lai,et al.  Cancellable iris template generation based on Indexing-First-One hashing , 2017, Pattern Recognit..

[9]  Sherali Zeadally,et al.  Anonymous biometrics-based authentication scheme with key distribution for mobile multi-server environment , 2017, Future Gener. Comput. Syst..

[10]  Fan Zhang,et al.  Spatio-Temporal Analysis of Passenger Travel Patterns in Massive Smart Card Data , 2017, IEEE Transactions on Intelligent Transportation Systems.

[11]  Jizhou Sun,et al.  Improvements of Juang 's Password-Authenticated Key Agreement Scheme Using Smart Cards , 2009, IEEE Transactions on Industrial Electronics.

[12]  Kien A. Hua,et al.  Linear Subspace Ranking Hashing for Cross-Modal Retrieval , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Ruhul Amin,et al.  Cryptanalysis and Efficient Dynamic ID Based Remote User Authentication Scheme in Multi-server Environment Using Smart Card , 2016, Int. J. Netw. Secur..

[14]  Ping Wang,et al.  Two Birds with One Stone: Two-Factor Authentication with Security Beyond Conventional Bound , 2018, IEEE Transactions on Dependable and Secure Computing.

[15]  Ahmad Tavassoli,et al.  Evaluation of effects from sample-size origin-destination estimation using smart card fare data , 2017 .

[16]  Carmen Forciniti,et al.  Factors influencing trip generation on metro system in Madrid (Spain) , 2019, Transportation Research Part D: Transport and Environment.