Human-Centric Authentication Systems for Secure Access Control in IoT-connected Autonomous Vehicles
Keywords:
International Data CorporationAbstract
User convenience, efficiency, and security must be kept in mind when proposing any new mechanism for authentication [1]. In the IoT-connected AV ecosystem, users interact with the in-vehicular infotainment and entertainment system (IETS), vehicle control system (VCS), and autonomous vehicle service control system (AVCS). These systems are composed of a variety of applications, including media players, voice assistant systems (VAS), internet browsing, in-vehicle vehicle-to-vehicle and vehicle-to-infrastructure (V2X) communication, GPS navigation, and various types of sensors. All the applications are operated via different input/output (I/O) modules, including touch screens, voice sensors, and smart wearable devices. Hence, we have proposed human-centric secure identification and access control for the involved IoT applications in different subsystems. Furthermore, we have proposed a system that can support distributed and edge computing environments as well as the cloud access control server.
Downloads
References
A. Ali, M. Ahmed, A. Khan, A. Anjum et al., "VisTAS: blockchain-based visible and trusted remote authentication system," 2021. ncbi.nlm.nih.gov
Tatineni, Sumanth, and Anjali Rodwal. “Leveraging AI for Seamless Integration of DevOps and MLOps: Techniques for Automated Testing, Continuous Delivery, and Model Governance”. Journal of Machine Learning in Pharmaceutical Research, vol. 2, no. 2, Sept. 2022, pp. 9-41, https://pharmapub.org/index.php/jmlpr/article/view/17.
Prabhod, Kummaragunta Joel. "Advanced Machine Learning Techniques for Predictive Maintenance in Industrial IoT: Integrating Generative AI and Deep Learning for Real-Time Monitoring." Journal of AI-Assisted Scientific Discovery 1.1 (2021): 1-29.
Tatineni, Sumanth, and Venkat Raviteja Boppana. "AI-Powered DevOps and MLOps Frameworks: Enhancing Collaboration, Automation, and Scalability in Machine Learning Pipelines." Journal of Artificial Intelligence Research and Applications 1.2 (2021): 58-88.
A. Ometov, V. Petrov, S. Bezzateev, S. Andreev et al., "Challenges of Multi-Factor Authentication for Securing Advanced IoT (A-IoT) Applications," 2019. [PDF]
P. Kumar Sadhu, V. P. Yanambaka, S. P. Mohanty, and E. Kougianos, "Easy-Sec: PUF-Based Rapid and Robust Authentication Framework for the Internet of Vehicles," 2022. [PDF]
I. Ali, S. Sabir, and Z. Ullah, "Internet of Things Security, Device Authentication and Access Control: A Review," 2019. [PDF]
S. Danba, J. Bao, G. Han, S. Guleng et al., "Toward Collaborative Intelligence in IoV Systems: Recent Advances and Open Issues," 2022. ncbi.nlm.nih.gov
V. R. Kebande, F. M. Awaysheh, R. A. Ikuesan, S. A. Alawadi et al., "A Blockchain-Based Multi-Factor Authentication Model for a Cloud-Enabled Internet of Vehicles," 2021. ncbi.nlm.nih.gov
S. Loredana Nita and M. Iulian Mihailescu, "Elliptic Curve-Based Query Authentication Protocol for IoT Devices Aided by Blockchain," 2023. ncbi.nlm.nih.gov
J. Li, J. Jin, L. Lyu, D. Yuan et al., "A Fast and Scalable Authentication Scheme in IoT for Smart Living," 2020. [PDF]
K. Istiaque Ahmed, M. Tahir, M. Hadi Habaebi, S. Lun Lau et al., "Machine Learning for Authentication and Authorization in IoT: Taxonomy, Challenges and Future Research Direction," 2021. ncbi.nlm.nih.gov
P. Nespoli, M. Zago, A. Huertas Celdrán, M. Gil Pérez et al., "PALOT: Profiling and Authenticating Users Leveraging Internet of Things," 2019. ncbi.nlm.nih.gov
W. Yang, S. Wang, N. Masri Sahri, N. M. Karie et al., "Biometrics for Internet-of-Things Security: A Review," 2021. ncbi.nlm.nih.gov
P. Shen Teh, A. Beng Jin Teoh, and S. Yue, "A Survey of Keystroke Dynamics Biometrics," 2013. ncbi.nlm.nih.gov
S. Uppuluri and G. Lakshmeeswari, "Secure user authentication and key agreement scheme for IoT device access control based smart home communications," 2022. ncbi.nlm.nih.gov
M. Grobler, R. Gaire, and S. Nepal, "User, Usage and Usability: Redefining Human Centric Cyber Security," 2021. ncbi.nlm.nih.gov
M. El-hajj, A. Fadlallah, M. Chamoun, and A. Serhrouchni, "A Survey of Internet of Things (IoT) Authentication Schemes †," 2019. ncbi.nlm.nih.gov
P. Xiong, S. Buffett, S. Iqbal, P. Lamontagne et al., "Towards a Robust and Trustworthy Machine Learning System Development: An Engineering Perspective," 2021. [PDF]
M. Elkhodr, S. Shahrestani, and H. Cheung, "The Internet of Things: New Interoperability, Management and Security Challenges," 2016. [PDF]
S. Duque Anton, D. Fraunholz, C. Lipps, K. Alam et al., "Putting Things in Context: Securing Industrial Authentication with Context Information," 2019. [PDF]
N. Singh, R. Buyya, and H. Kim, "Securing Cloud-Based Internet of Things: Challenges and Mitigations," 2024. [PDF]
M. Umar Aftab, A. Oluwasanmi, A. Alharbi, O. Sohaib et al., "Secure and dynamic access control for the Internet of Things (IoT) based traffic system," 2021. ncbi.nlm.nih.gov
M. Gupta, J. Benson, F. Patwa, and R. Sandhu, "Secure Cloud Assisted Smart Cars Using Dynamic Groups and Attribute Based Access Control," 2019. [PDF]
P. Gaba, R. Shringar Raw, O. Kaiwartya, and M. Aljaidi, "B-SAFE: Blockchain-Enabled Security Architecture for Connected Vehicle Fog Environment †," 2024. ncbi.nlm.nih.gov
R. H. Hsu, J. Lee, T. Q. S. Quek, and J. C. Chen, "Reconfigurable Security: Edge Computing-based Framework for IoT," 2017. [PDF]
P. Kumar Sadhu, V. P. Yanambaka, and A. Abdelgawad, "Internet of Things: Security and Solutions Survey," 2022. ncbi.nlm.nih.gov
K. Gopalakrishnan, A. Balakrishnan, K. Govardhanan, and S. Selvarasu, "Propositional Inference for IoT Based Dosage Calibration System Using Private Patient-Specific Prescription against Fatal Dosages," 2022. ncbi.nlm.nih.gov
Y. Zhang and X. Wu, "Access Control in Internet of Things: A Survey," 2016. [PDF]
T. Mawla, M. Gupta, S. Ameer, and R. Sandhu, "The ACAC_D Model for Mutable Activity Control and Chain of Dependencies in Smart and Collaborative Systems," 2023. [PDF]
D. Chamorro and G. Vergara-Hermosilla, "Lebesgue spaces with variable exponent: some applications to the Navier-Stokes equations," 2023. [PDF]
R. Xu, Y. Chen, E. Blasch, and G. Chen, "BlendCAC: A BLockchain-ENabled Decentralized Capability-based Access Control for IoTs," 2018. [PDF]
R. Xu, Y. Chen, E. Blasch, and G. Chen, "A Federated Capability-based Access Control Mechanism for Internet of Things (IoTs)," 2018. [PDF]
S. Paiva, M. Abdul Ahad, G. Tripathi, N. Feroz et al., "Enabling Technologies for Urban Smart Mobility: Recent Trends, Opportunities and Challenges," 2021. ncbi.nlm.nih.gov
Y. Chen, X. Wang, Y. Yang, and H. Li, "Location-Aware Wi-Fi Authentication Scheme Using Smart Contract," 2020. ncbi.nlm.nih.gov
H. Fang, A. Qi, and X. Wang, "Fast Authentication and Progressive Authorization in Large-Scale IoT: How to Leverage AI for Security Enhancement?," 2019. [PDF]
T. Liu, F. Sabrina, J. Jang-Jaccard, W. Xu et al., "Artificial Intelligence-Enabled DDoS Detection for Blockchain-Based Smart Transport Systems," 2021. ncbi.nlm.nih.gov
O. Cheikhrouhou, I. Amdouni, K. Mershad, M. Ammi et al., "Blockchain for the Cybersecurity of Smart City Applications," 2022. [PDF]
U. Khalil, O. Ahmed Malik, M. Uddin, and C. L. Chen, "A Comparative Analysis on Blockchain versus Centralized Authentication Architectures for IoT-Enabled Smart Devices in Smart Cities: A Comprehensive Review, Recent Advances, and Future Research Directions," 2022. ncbi.nlm.nih.gov