Robotics-Driven Biometric Authentication for Secure and Intelligent Vehicle Access

Authors

  • Vishnu G. Nair Manipal Academy of Higher Education https://orcid.org/0000-0003-0599-748X
  • Madala Chaitanya Sai Manipal Academy of Higher Education
  • Spoorthi Singh Manipal Academy of Higher Education
  • Navya Thirumaleswar Hegde Manipal Academy of Higher Education
  • Manish Varun Yadav Manipal Academy of Higher Education

DOI:

https://doi.org/10.18196/jrc.v6i5.26057

Keywords:

Biometric Authentication, Artificial Intelligence, Cyber-Physical Security, Robotics Integration, Vehicle Access Control, Data Privacy

Abstract

As modern vehicles increasingly adopt intelligent systems, the need for robust and secure access control mechanisms has become paramount. This study presents a dual modal biometric authentication framework integrating fingerprint and iris recognition to enhance vehicular security and user convenience. The system leverages strategically positioned sensors—capacitive fingerprint scanners embedded within door handles and high-resolution iris scanners mounted near the driver’s entry point—coupled with a central microcontroller for real-time processing. Lightweight image processing and matching algorithms are implemented to ensure fast and accurate authentication under varied environmental conditions. The proposed system was validated on a prototype vehicle model using biometric data from over 50 users, demonstrating high accuracy, low false acceptance/rejection rates, and resilience to spoofing attacks. In addition to technical implementation, the study addresses practical challenges including sensor placement, processing constraints, data privacy, and system usability. The findings support the feasibility of integrating multimodal biometric authentication in vehicles, offering a secure, user-friendly alternative to conventional key- based systems. This research is supported by Indian patent file number 202441019532.

Author Biography

Vishnu G. Nair, Manipal Academy of Higher Education

Dr. Vishnu G Nair (MTech, MBA, Ph.D., LMISTE, MIET)  Associate Professor Department of Aeronautical and Automobile Engineering  Manipal Institute of Technology  Manipal Academy of Higher Education Manipal Karnataka India- 576104 Mob: +91 8722633300

References

G. B. Loganathan, “CAN Based Automated Vehicle Security System,” International Journal of Mechanical Engineering and Technology, vol. 10, no. 7, 2019.

P. Singh, T. Sethi, B. K. Balabantaray, and B. B. Biswal, “Advanced vehicle security system,” in ICIIECS 2015 - 2015 IEEE International Conference on Innovations in Information, Embedded and Communication Systems, pp. 1–6, 2015, doi: 10.1109/ICIIECS.2015.7193276.

R. Prashantkumar, S. Sagar, Nambiar, and Siddharth, “Two-wheeler vehicle security system,” International Journal of Engineering Sciences and Emerging Technologies, pp. 324–334, 2013.

K. Koscher et al., “Experimental security analysis of a modern automobile,” in Proceedings - IEEE Symposium on Security and Privacy, pp. 447–462, 2010, doi: 10.1109/SP.2010.34.

R. Prashantkumar, S. Sagar, Nambiar, and Siddharth, “A 3D Iris Scanner from a Single Image Using Convolutional Neural Networks,” IEEE Access, vol. 8, pp. 98584–98599, 2020.

K. Hollingsworth, K. W. Bowyer, and P. J. Flynn, “Pupil dilation degrades iris biometric performance,” Computer Vision and Image Understanding, vol. 113, no. 1, pp. 150–157, 2009.

F. N. Sibai, H. I. Hosani, R. M. Naqbi, S. Dhanhani, and S. Shehhi, “Iris recognition using artificial neural networks,” Expert Systems with Applications, vol. 38, no. 5, pp. 5940–5946, 2011.

M. Tartagni and R. Guerrieri, “A fingerprint sensor based on the feedback capacitive sensing scheme,” IEEE Journal of Solid-State Circuits, vol. 33, no. 1, pp. 133–142, 1998.

F. Hidayanti, F. Rahmah, and A. Wiryawan, “Design of motorcycle security system with fingerprint sensor using arduino uno microcontroller,” International Journal of Advanced Science and Technology, vol. 29, no. 5, pp. 4374–4391, 2020.

A. Sharma, D. Kumar, and G. Gupta, “Enhanced Iris Recognition with Histogram Cut Selection and Genetic Algorithms for Robust Classification,” Procedia Computer Science, vol. 258, pp. 2846-2859, 2025.

F. D. Garcia, D. Oswald, T. Kasper, and P. Pavlidès, “Lock it and still lose it – on the (in)security of automotive remote keyless entry systems,” in Proceedings of the 25th USENIX Security Symposium, pp. 929–944, 2016.

S. Arora and M. P. S. Bhatia, “Challenges and opportunities in biometric security: A survey,” Information Security Journal, vol. 31, no. 1, pp. 28–48, 2022, doi: 10.1080/19393555.2021.1873464.

M. Faundez-Zanuy, “Biometric security technology,” IEEE Aerospace and Electronic Systems Magazine, vol. 21, no. 6, pp. 15–26, 2006, doi: 10.1109/MAES.2006.1662038.

A. K. Jain, A. Ross, and S. Prabhakar, “An Introduction to Biometric Recognition,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 14, no. 1, pp. 4–20, 2004, doi: 10.1109/TCSVT.2003.818349.

J. G. Daugman, “High Confidence Visual Recognition of Persons by a Test of Statistical Independence,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 11, pp. 1148–1161, 1993, doi: 10.1109/34.244676.

S. Punnoose and J. S. J. Kumar, “Iris Recognition for Security & Safety of Automobiles,” International Journal of Innovative Science, Engineering & Technology, vol. 2, no. 4, pp. 961–966, 2015.

Z. M. Win and M. M. Sein, “Fingerprint recognition system for low quality images,” in Proceedings of the SICE Annual Conference, vol. 2, no. 4, pp. 1133–1137, 2011.

Kiruthiga Narayanasamy, “A Study of Biometric Approach for Vehicle Security System Using Fingerprint Recognition,” International Journal of Advanced Research Trends in Engineering and Technology (IJARTET), vol. 1, no. 2, pp. 10–14, 2014.

K. Vishi and S. Y. Yayilgan, “Multimodal biometric authentication using fingerprint and iris recognition in identity management,” in Proceedings - 2013 9th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2013, pp. 334–341, 2013, doi: 10.1109/IIH-MSP.2013.91.

A. Ometov and S. Bezzateev, “Multi-factor authentication: A survey and challenges in V2X applications,” in International Congress on Ultra-Modern Telecommunications and Control Systems and Workshops, pp. 129–136, 2017, doi: 10.1109/ICUMT.2017.8255200.

G. Babu and M. Soniya, “IoT based Intelligent Car Security System using IRIS image features,” Journal of Physics: Conference Series, vol. 1, 2021.

C. Lupu and V. Lupu, “Multimodal biometrics for access control in an intelligent car,” in ISCIII’07: 3rd International Symposium on Computational Intelligence and Intelligent Informatics; Proceedings, vol. 1, no. 2, pp. 261–267, 2007, doi: 10.1109/ISCIII.2007.367399.

G. Reshma, B. T. Prasanna, H. S. N. Murthy, T. S. N. Murthy, S. Parthiban, and M. Sangeetha, “Privacy-aware access control (PAAC)-based biometric authentication protocol (Bap) for mobile edge computing environment,” Soft Computing, 2023, doi: 10.1007/s00500-023-08226-5.

P. J. Mehta, B. L. Parne, and S. J. Patel, “SE-LAKAF: Security enhanced lightweight authentication and key agreement framework for smart grid network,” Peer-to-Peer Networking and Applications, vol. 16, no. 3, pp. 1513–1535, 2023, doi: 10.1007/s12083-023-01494-w.

X. Duan, Y. Guo, and Y. Guo, “Design of anonymous authentication scheme for vehicle fog services using blockchain,” Wireless Networks, vol. 30, no. 1, pp. 193–207, 2024, doi: 10.1007/s11276-023-03471-w.

N. Kaliya and D. Pawar, “Unboxing fog security: a review of fog security and authentication mechanisms,” Computing, vol. 105, no. 12, pp. 2793–2819, 2023, doi: 10.1007/s00607-023-01208-3.

S. R. Borra et al., “Deep hashing with multilayer CNN-based biometric authentication for identifying individuals in transportation security,” Journal of Transportation Security, vol. 17, no. 1, 2024, doi: 10.1007/s12198-024-00272-w.

T. Kaur et al., “Development, detection and decipherment of obfuscated fingerprints in humans: Implications for forensic casework,” Science of Nature, vol. 110, no. 6, 2023, doi: 10.1007/s00114-023-01886-1.

D. Das, S. Banerjee, and U. Biswas, “A secure vehicle theft detection framework using Blockchain and smart contract,” Peer-to-Peer Networking and Applications, vol. 14, no. 2, pp. 672–686, 2021, doi: 10.1007/s12083-020-01022-0.

D. Das, S. Banerjee, U. Ghosh, U. Biswas, and A. K. Bashir, “A decentralized vehicle anti-theft system using Blockchain and smart contracts,” Peer-to-Peer Networking and Applications, vol. 14, no. 5, pp. 2775–2788, 2021, doi: 10.1007/s12083-021-01097-3.

F. Qazi, S. A. Khan, F. Hanif, and D. E. S. Agha, “Efficient Routing Algorithm Towards the Security of Vehicular Ad-Hoc Network and Its Applications,” International Journal of Wireless Information Networks, vol. 31, no. 1, pp. 12–28, 2024, doi: 10.1007/s10776-023-00613-x.

M. A. Akram, A. N. Mian, and S. Kumari, “Fog-based low latency and lightweight authentication protocol for vehicular communication,” Peer-to-Peer Networking and Applications, vol. 16, no. 2, pp. 629–643, 2023, doi: 10.1007/s12083-022-01425-1.

S. Shomaji, Z. Guo, F. Ganji, N. Karimian, D. Woodard, and D. Forte, “BLOcKeR: A Biometric Locking Paradigm for IoT and the Connected Person,” Journal of Hardware and Systems Security, vol. 5, no. 3–4, pp. 223–236, 2021, doi: 10.1007/s41635-021-00121-5.

M. Hernandez-de-Menendez, R. Morales-Menendez, C. A. Escobar, and J. Arinez, “Biometric applications in education,” International Journal on Interactive Design and Manufacturing, vol. 15, no. 2–3, pp. 365–380, 2021, doi: 10.1007/s12008-021-00760-6.

R. Sujarani, D. Manivannan, R. Manikandan, and B. Vidhyacharan, “Lightweight Bio-Chaos Crypt to Enhance the Security of Biometric Images in Internet of Things Applications,” Wireless Personal Communications, vol. 119, no. 3, pp. 2517–2537, 2021, doi: 10.1007/s11277-021-08342-1.

A. Goswami, S. Rana, and D. Chhikara, “An efficient blockchain assisted dynamic authentication scheme for geo-spatial enabled vehicular network,” Telecommunication Systems, vol. 83, no. 3, pp. 241–251, 2023, doi: 10.1007/s11235-023-01016-2.

R. Shikka, R. Kamalraj, P. K. Shah, K. Sutariya, S. R. Anwar, and A. Kumar, “Intelligent algorithms in privacy-preserving authentication schemes and traceability with accuracy in VANETs for smart transportation,” Soft Computing, vol. 28, no. 23, pp. 13853–13862, 2024, doi: 10.1007/s00500-023-08634-7.

G. Kumar and A. Altalbe, “Artificial intelligence (AI) advancements for transportation security: in-depth insights into electric and aerial vehicle systems,” Environment, Development and Sustainability, 2024, doi: 10.1007/s10668-024-04790-4.

S. A. Sivasankari, D. Gupta, I. Keshta, C. V. K. Reddy, P. P. Singh, and H. Byeon, “Anonymity and security improvements in heterogeneous connected vehicle networks,” International Journal of Data Science and Analytics, vol. 19, no. 4, pp. 749–762, 2025, doi: 10.1007/s41060-023-00499-1.

K. Bayoudh, R. Knani, F. Hamdaoui, and A. Mtibaa, “A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets,” Visual Computer, vol. 38, no. 8, pp. 2939–2970, 2022, doi: 10.1007/s00371-021-02166-7.

S. M. Taylor and M. De Leeuw, “Guidance systems: from autonomous directives to legal sensor-bilities,” AI and Society, vol. 36, no. 2, pp. 521–534, 2021, doi: 10.1007/s00146-020-01012-z.

S. Quach, P. Thaichon, K. D. Martin, S. Weaven, and R. W. Palmatier, “Digital technologies: tensions in privacy and data,” Journal of the Academy of Marketing Science, vol. 50, no. 6, pp. 1299–1323, 2022, doi: 10.1007/s11747-022-00845-y.

M. Xiao, L. Chen, H. Feng, Z. Peng, and Q. Long, “Smart City Public Transportation Route Planning Based on Multi-objective Optimization: A Review,” Archives of Computational Methods in Engineering, vol. 31, no. 6, pp. 3351–3375, 2024, doi: 10.1007/s11831-024-10076-9.

V. L. Raposo, “The Use of Facial Recognition Technology by Law Enforcement in Europe: a Non-Orwellian Draft Proposal,” European Journal on Criminal Policy and Research, vol. 29, no. 4, pp. 515–533, 2023, doi: 10.1007/s10610-022-09512-y.

M. Khare, A. Khare, M. Jeon, and I. K. Sethi, “Machine vision theory and applications for cyber-physical systems,” Multimedia Tools and Applications, vol. 81, no. 16, pp. 21995–22000, 2022, doi: 10.1007/s11042-022-13261-9.

Arshi and Mondal, “Smart Construction and Sustainable Cities Advancements in sensors and actuators technologies for smart cities: a comprehensive review,” Smart Construction and Sustainable Cities, vol. 1, no. 18, 2023.

L. Yang et al., “Exploring the role of computer vision in product design and development: a comprehensive review,” International Journal on Interactive Design and Manufacturing, vol. 18, no. 6, pp. 3633–3680, 2024, doi: 10.1007/s12008-024-01765-7.

V. Rao and K. V. Prema, “A review on lightweight cryptography for Internet-of-Things based applications,” Journal of Ambient Intelligence and Humanized Computing, vol. 12, no. 9, pp. 8835–8857, 2021, doi: 10.1007/s12652-020-02672-x.

L. Rachakonda, A. K. Bapatla, S. P. Mohanty, and E. Kougianos, “BACTmobile: A Smart Blood Alcohol Concentration Tracking Mechanism for Smart Vehicles in Healthcare CPS Framework,” SN Computer Science, vol. 3, no. 3, 2022, doi: 10.1007/s42979-022-01142-9.

C. B. Tan et al., “A survey on presentation attack detection for automatic speaker verification systems: State-of-the-art, taxonomy, issues and future direction,” Multimedia Tools and Applications, vol. 80, no. 21–23, pp. 32725–32762, 2021, doi: 10.1007/s11042-021-11235-x.

R. De Smet, T. Vandervelden, K. Steenhaut, and A. Braeken, “Lightweight PUF based authentication scheme for fog architecture,” Wireless Networks, vol. 27, no. 2, pp. 947–959, 2021, doi: 10.1007/s11276-020-02491-0.

S. Rana, D. Mishra, C. Lal, and M. Conti, “Authenticated Message-Exchange Protocol for Fog-Assisted Vehicular Cloud Computing,” Wireless Personal Communications, vol. 131, no. 2, pp. 1295–1312, 2023, doi: 10.1007/s11277-023-10480-7.

H. S. Grover, Adarsh, and D. Kumar, “Cryptanalysis and improvement of a three-factor user authentication scheme for smart grid environment,” Journal of Reliable Intelligent Environments, vol. 6, pp. 249–260, 2020.

J. P. A. Yaacoub, H. N. Noura, O. Salman, and A. Chehab, “Robotics cyber security: vulnerabilities, attacks, countermeasures, and recommendations,” International Journal of Information Security, vol. 21, no. 1, pp. 115–158, 2022, doi: 10.1007/s10207-021-00545-8.

A. Alagumalai et al., “Self-powered sensing systems with learning capability,” Joule, vol. 6, no. 7, pp. 1475–1500, 2022, doi: 10.1016/j.joule.2022.06.001.

A. K. Tyagi and S. U. Aswathy, “Autonomous Intelligent Vehicles (AIV): Research statements, open issues, challenges and road for future,” International Journal of Intelligent Networks, vol. 2, pp. 83–102, 2021, doi: 10.1016/j.ijin.2021.07.002.

P. Y. Tseng, P. C. Lin, and E. Kristianto, “Vehicle theft detection by generative adversarial networks on driving behavior,” Engineering Applications of Artificial Intelligence, vol. 117, 2023, doi: 10.1016/j.engappai.2022.105571.

Z. Chen, X. Feng, and S. Zhang, “Emotion detection and face recognition of drivers in autonomous vehicles in IoT platform,” Image and Vision Computing, vol. 128, 2022, doi: 10.1016/j.imavis.2022.104569.

S. T. Banafshehvaragh and A. M. Rahmani, “Intrusion, anomaly, and attack detection in smart vehicles,” Microprocessors and Microsystems, vol. 96, 2023, doi: 10.1016/j.micpro.2022.104726.

F. Alwahedi, A. Aldhaheri, M. A. Ferrag, A. Battah, and N. Tihanyi, “Machine learning techniques for IoT security: Current research and future vision with generative AI and large language models,” Internet of Things and Cyber-Physical Systems, vol. 4, pp. 167–185, 2024, doi: 10.1016/j.iotcps.2023.12.003.

B. D. Deebak, “Lightweight authentication and key management in mobile-sink for smart IoT-assisted systems,” Sustainable Cities and Society, vol. 63, 2020, doi: 10.1016/j.scs.2020.102416.

M. H. Khan, A. R. Javed, Z. Iqbal, M. Asim, and A. I. Awad, “DivaCAN: Detecting in-vehicle intrusion attacks on a controller area network using ensemble learning,” Computers and Security, vol. 139, pp. 947–959, 2024, doi: 10.1016/j.cose.2024.103712.

R. Casanova-Marqués, J. Torres-Sospedra, J. Hajny, and M. Gould, “Maximizing privacy and security of collaborative indoor positioning using zero-knowledge proofs,” Internet of Things (Netherlands), vol. 22, 2023, doi: 10.1016/j.iot.2023.100801.

G. Sabaliauskaite, J. Bryans, H. Jadidbonab, F. Ahmad, S. Shaikh, and P. Wooderson, “TOMSAC - Methodology for trade-off management between automotive safety and cyber security,” Computers and Security, vol. 140, 2024, doi: 10.1016/j.cose.2024.103798.

Y. Guo and Y. Guo, “FogHA: An efficient handover authentication for mobile devices in fog computing,” Computers and Security, vol. 108, 2021, doi: 10.1016/j.cose.2021.102358.

P. Mundhe, S. Verma, and S. Venkatesan, “A comprehensive survey on authentication and privacy-preserving schemes in VANETs,” Computer Science Review, vol. 41, p. 100411, 2021, doi: 10.1016/j.cosrev.2021.100411.

A. Kumar, R. Saha, M. Conti, G. Kumar, W. J. Buchanan, and T. H. Kim, “A comprehensive survey of authentication methods in Internet-of-Things and its conjunctions,” Journal of Network and Computer Applications, vol. 204, 2022, doi: 10.1016/j.jnca.2022.103414.

F. Ghaffari, E. Bertin, N. Crespi, and J. Hatin, “Distributed ledger technologies for authentication and access control in networking applications: A comprehensive survey,” Computer Science Review, vol. 50, 2023, doi: 10.1016/j.cosrev.2023.100590.

D. Dharminder, U. Kumar, and P. Gupta, “Edge based authentication protocol for vehicular communications without trusted party communication,” Journal of Systems Architecture, vol. 119, 2021, doi: 10.1016/j.sysarc.2021.102242.

M. S. Almadani, S. Alotaibi, H. Alsobhi, and O. K. Hussain, “Blockchain-based multi-factor authentication: A systematic literature review,” Internet of Things, vol. 23, 2023.

J. W. Lee, W. K. Lee, and S. Y. Sohn, “Patenting trends in biometric technology of the Big Five patent offices,” World Patent Information, vol. 65, 2021, doi: 10.1016/j.wpi.2021.102040.

Z. T. Pritee, M. H. Anik, S. B. Alam, J. R. Jim, M. M. Kabir, and M. F. Mridha, “Machine learning and deep learning for user authentication and authorization in cybersecurity: A state-of-the-art review,” Computers and Security, vol. 140, 2024, doi: 10.1016/j.cose.2024.103747.

H. Yang, Y. Guo, and Y. Guo, “Blockchain-based cloud-fog collaborative smart home authentication scheme,” Computer Networks, vol. 242, 2024, doi: 10.1016/j.comnet.2024.110240.

Z. Wang, D. Deng, S. Hou, Y. Guo, and S. Li, “Design of three-factor secure and efficient authentication and key-sharing protocol for IoT devices,” Computer Communications, vol. 203, pp. 1–14, 2023, doi: 10.1016/j.comcom.2023.02.015.

M. Kokila and S. Reddy K, “Authentication, access control and scalability models in Internet of Things Security–A review,” Cyber Security and Applications, vol. 3, 2025, doi: 10.1016/j.csa.2024.100057.

P. Srinivasan, S. Anthoniraj, K. Anguraj, S. Kumarganesh, and B. Thiyaneswaran, “Development of keyless biometric authenticated vehicles ignition system,” Materials Today: Proceedings, vol. 81, no. 2, pp. 464–469, 2021, doi: 10.1016/j.matpr.2021.03.632.

B. Khalid, K. N. Qureshi, K. Z. Ghafoor, and G. Jeon, “An improved biometric based user authentication and key agreement scheme for intelligent sensor based wireless communication,” Microprocessors and Microsystems, vol. 96, 2023, doi: 10.1016/j.micpro.2022.104722.

E. Haodudin Nurkifli and T. Hwang, “Provably secure authentication for the internet of vehicles,” Journal of King Saud University - Computer and Information Sciences, vol. 35, no. 8, 2023, doi: 10.1016/j.jksuci.2023.101721.

A. I. Awad, A. Babu, E. Barka, and K. Shuaib, “AI-powered biometrics for Internet of Things security: A review and future vision,” Journal of Information Security and Applications, vol. 82, 2024, doi: 10.1016/j.jisa.2024.103748.

V. Kumar, “RSFVC: Robust Biometric-Based Secure Framework for Vehicular Cloud Networking,” IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 5, pp. 3364–3374, 2024, doi: 10.1109/TITS.2023.3322960.

M. Tanveer, A. U. Khan, H. Shah, S. A. Chaudhry, and A. Naushad, “PASKE-IoD: Privacy-Protecting Authenticated Key Establishment for Internet of Drones,” IEEE Access, vol. 9, pp. 145683–145698, 2021, doi: 10.1109/ACCESS.2021.3123142.

Downloads

Published

2025-09-02

How to Cite

[1]
V. G. Nair, M. C. Sai, S. Singh, N. T. Hegde, and M. V. Yadav, “Robotics-Driven Biometric Authentication for Secure and Intelligent Vehicle Access”, J Robot Control (JRC), vol. 6, no. 5, pp. 2184–2199, Sep. 2025.

Issue

Section

Articles

Most read articles by the same author(s)