A highly secure Multi- Factor authentication system using biometrics to enhance privacy in Internet of Things (IOT)

  • Vijay M Assistant Professor, Department of ECE & V.S.B. Engineering College, Karur,Tamil Nadu, India.
  • Indumathi G Professor, Department of ECE & Mepco Schlenk Engineering College, Sivakasi,Tamil Nadu, India.
Keywords: Biometrics, ECC, MB-LBP, OTP


Authentication is becoming critical in the Internet of Things (IoT) environment because of its many applications and services have been emerging in the areas such as smart city, healthcare, industry etc. Security and privacy plays a vital role in IoT because their services can be accessed through smart device applications by the user from everywhere and at any time. Hence a multi-factor based authentication can provide high security in IOT environment. This security system incorporates most of the valuable methods such as cryptography, steganography and pattern recognition for authentication process. Among various biometric traits, palm vein is more efficient because it has essential sufficient features points for individual unique identification. The system employs registration phase and authentication phase.  The registration phase enrolls person privacy data with their biometric and the obtained data’s are encrypted with the help of Elliptical Curve Cryptography (ECC) and this confidential information is embedded into person palm print image using bits substitution procedure. In authentication phase, recognition will be performed through three levels such as password, palm print and One Time Password (OTP). Using these three levels the matching can be done. The texture features can be obtained by using Multi Block Local Binary Pattern (MB-LBP) and Gabor filter. To afford high authentication, OTP method is also appended. This system provides better information security and texture analysis rather than previous approaches. Thus this multiple level approach ensures a fool proof and a reliable way for data access. Results are in terms of some validation parameters like false acceptance ratio, false rejection ratio and recognition rate. Observing from results, it is clear that the proposed approach outperform many existing methods. As a result, the proposed scheme has strong security, reliability and enhanced computational efficiency.


[1] Hong Liu and Yanbing Liu, “Cryptanalyzing an Image Encryption Scheme based on Hybrid Chaotic System and Cyclic Elliptic Curve”, In Optics and Laser Technology, Elsevier, vol. 56, pp. 15–19, (2014).
[2] S. Maria Celestin Vigila and K. Muneeswaran, “Nonce Based Elliptic Curve Cryptosystem for Text and Image Applications”, in International Journal of Network Security, vol. 14, no. 4, pp. 236–242, July (2012).
[3] S. Behnia, A. Akhavan, A. Akhshani and A. Samsudin, “Image Encryption based on the Jacobian Elliptic Maps”, In The Journal of System and Software, Elsevier, vol. 86, pp. 2429–2438, (2013).
[4] Li Li, Ahmed A. Abd El-Latif and XiamuNiu, “Elliptic Curve ElGamal Based Homomorphic Image Encryption Scheme for Sharing Secret Images”, In: Signal Processing, Elsevier, vol. 92, pp. 1069–1078, (2012).
[5] Don Johnson, Alfred Menezes and Scott Vanstone, “The Elliptic Curve Digital Signature Algorithm (ECDSA)”, Certicom Corporation, (2001).
[6] Lo’aiTawalbeh, MoadMowafi and WalidAljoby, “Use of Elliptic Curve Cryptography for Multimedia Encryption”, IET Information Security, vol. 7, issue 2, pp. 67–74, (2012).
[7] I KetutGedeDarma Putra, Erdiawan, “High Performance Palmprint Identification System Based On Two Dimensional Gabor” TELKOMNIKA Vol. 8, No. 3, pp.309-318, 2010.
[8] Kai Liu; Seungbin Moon “Robust dual-stage face recognition method using PCA and high-dimensional-LBP” IEEE International Conference on Information and Automation (ICIA), 2016
[9] Aditya Nigam; Phalguni Gupta, “Tri-modal biometric fusion for human authentication by tracking Differential Code Pattern” IEEE Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG),2016
[10] Therry Z. Lee; David B. L. Bong,” Face and palmprint multimodal biometric system based on bit-plane decomposition approach “IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW), 2016
[11] AkhmadFaizal Akbar; TjokordaAgung Budi Wirayudha; Mahmud DwiSulistiyo, “Palm vein biometric identification system using local derivative pattern”, IEEE International Conference on Information and Communication Technology (ICoICT), 2016
[12] RaouiaMokni; MonjiKherallah “Novel palmprint biometric system combining several fractal methods for texture information extraction” IEEE International Conference on Systems, Man, and Cybernetics (SMC), February 2017
[13] R. Parkavi; K. R. Chandeesh Babu; J. Ajeeth Kumar “Multimodal Biometrics for user authentication” IEEE International Conference on: Intelligent Systems and Control (ISCO), 2017
[14] S. Veluchamy; L. R. Karlmarx “System for multimodal biometric recognition based on finger knuckle and finger vein using feature-level fusion and k-support vector machine classifier”, IET Biometrics Volume: 6, Issue: 3, 2017
[15] KrishnasreeVasagiri; SudhakarRaoParvata “Dorsal hand vein Biometric authentication using complex Walsh transform”, IEEE International Conference on Applied and Theoretical Computing and Communication Technology (ICATCCT), 2017.
[16] Druva Kumar L; Goutham Reddy Alavalapati “Biometric authentication using near infrared hand vein pattern with adaptive threshold technique”, “IEEE International Conference on Applied and Theoretical Computing and Communication Technology (ICATCCT),2017.
[17] John Jenkins; Joseph Shelton; Kaushik Roy “One-time password for biometric systems: disposable feature templates”Southeast Con, 2017 ISSN: 1558-058X.
[18] P. Cancian; G. W. Di Donato; V. Rana; M. D. Santambrogio “An embedded Gabor-based palm vein recognition system”,IEEE EMBS International Conference on Biomedical& Health Informatics (BHI), 2017.
[19] A.Maheshwari, M. A. DoraiRangaswamy ‘”Multimodal Biometrics Security System For Authentication” 2016 Second International Conference on Science Technology Engineering and Management (ICONSTEM)
How to Cite
M, V., & G, I. (2019). A highly secure Multi- Factor authentication system using biometrics to enhance privacy in Internet of Things (IOT). International Research Journal of Multidisciplinary Technovation, 1(6), 26-34. Retrieved from https://mapletreejournals.com/index.php/irjmt/article/view/258