IJBTT

IoT Security Techniques Based On Machine Learning: How IoT Devices use AI to Enhance Security

	International Journal of Computer Trends and Technology (IJCTT)
	© 2019 by IJCTT Journal
	Volume-67 Issue-2
	Year of Publication : 2019
	Authors : Lakshmisri Surya
	DOI :  10.14445/22312803/IJCTT-V67I2P110

MLA Style: Lakshmisri Surya, "IoT Security Techniques Based On Machine Learning: How IoT Devices use AI to Enhance Security" International Journal of Computer Trends and Technology 67.2 (2019): 65-68.

APA Style:Lakshmisri Surya, (2019). IoT Security Techniques Based On Machine Learning: How IoT Devices use AI to Enhance Security. International Journal of Computer Trends and Technology, 67(2), 65-68.

Abstract
The internet of things (IoT) integrates various devices within the network to come up with intelligent and advanced services that help protect the privacy of the user and attacks, which includes eavesdropping, jamming, denial of service (DOS) attacks, and spoofing attacks. This research paper investigates the model used by IoT systems in cooperation with AI to enhance devices` security. The report also reviews IoT security solutions focused on machine learning technology, which includes reinforcement of learning, unsupervised learning, and supervised learning. The article also focuses on IoT malware detection, secure offloading, access control, and authentication techniques based on machine learning, which is AI. Additionally, the paper addresses the challenges which need to be investigated and addressed when implementing these machine learning schemes of security in IoT systems practically. IoT celebrated as the next technological revolution`s enabler would involve easy accessibility across extreme security, complex service mobility and context-aware, and cellular network networks. Thus, AI can play a significant role in the technology of the network infrastructure. However, by using the principles, instruments, and technologies of AI in cellular connections used by IoT, a range of problems will surface. The fundamental issues in using AI in wireless information systems that enable end-to-end IoT connectivity with possible comprehensive future research directions and solutions are addressed in this paper.

Reference
[1] Abbasi, M. A., Memon, Z. A., Memon, J., Syed, T. Q., & Alshboul, R. (2017). Addressing the future data management challenges in iot: A proposed framework. International Journal of Advanced Computer Science and Applications, 8(5), 197-207.
[2] Banafa, A. (2017). Three major challenges facing iot. IEEE Internet of things.
[3] Calo, S. B., Touna, M., Verma, D. C., & Cullen, A. (2017, December). Edge computing architecture for applying AI to IoT. In 2017 IEEE International Conference on Big Data (Big Data) (pp. 3012-3016). IEEE.
[4] Canedo, J., & Skjellum, A. (2016, December). Using machine learning to secure IoT systems. In 2016 14th annual conference on privacy, security and trust (PST) (pp. 219-222). IEEE.
[5] Deshpande, A., Pitale, P., & Sanap, S. (2016). Industrial automation using Internet of Things (IOT). International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), 5(2), 266-269.
[6] Lee, J. H., & Kim, H. (2017). Security and privacy challenges in the internet of things [security and privacy matters]. IEEE Consumer Electronics Magazine, 6(3), 134-136.
[7] Lu, R., Heung, K., Lashkari, A. H., & Ghorbani, A. A. (2017). A lightweight privacy-preserving data aggregation scheme for fog computing-enhanced IoT. IEEE Access, 5, 3302-3312.
[8] Madakam, S., & Date, H. (2016). Security mechanisms for connectivity of smart devices in the internet of things. In Connectivity frameworks for smart devices (pp. 23-41). Springer, Cham.
[9] Osuwa, A. A., Ekhoragbon, E. B., & Fat, L. T. (2017, September). Application of artificial intelligence in Internet of Things. In 2017 9th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 169-173). IEEE.
[10] Rehman, H. U., Asif, M., & Ahmad, M. (2017, December). Future applications and research challenges of IOT. In 2017 International conference on information and communication technologies (ICICT) (pp. 68-74). IEEE.
[11] Ren, Z., Liu, X., Ye, R., & Zhang, T. (2017, July). Security and privacy on internet of things. In 2017 7th IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC) (pp. 140-144). IEEE.
[12] Rutledge, R. L., Massey, A. K., & Antón, A. I. (2016, September). Privacy impacts of IoT devices: A SmartTV case study. In 2016 IEEE 24th International Requirements Engineering Conference Workshops (REW) (pp. 261-270). IEEE.
[13] Sha, K., Errabelly, R., Wei, W., Yang, T. A., & Wang, Z. (2017, May). Edgesec: Design of an edge layer security service to enhance iot security. In 2017 IEEE 1st International Conference on Fog and Edge Computing (ICFEC) (pp. 81-88). IEEE.
[14] Tripathy, B. K., & Anuradha, J. (Eds.). (2017). Internet of things (IoT): technologies, applications, challenges and solutions. CRC Press.
[15] Xiao, L., Wan, X., Lu, X., Zhang, Y., & Wu, D. (2018). IoT security techniques based on machine learning: How do IoT devices use AI to enhance security?. IEEE Signal Processing Magazine, 35(5), 41-49.
[16] Yang, Y., Wu, L., Yin, G., Li, L., & Zhao, H. (2017). A survey on security and privacy issues in Internet-of-Things. IEEE Internet of Things Journal, 4(5), 1250-1258.
[17] Yukitake, T. (2017, June). Innovative solutions toward future society with AI, Robotics, and IoT. In 2017 Symposium on VLSI Circuits (pp. C16-C19). IEEE.

Keywords
Machine learning, Artificial Intelligence, Cloud Computing, Cyber threats, and IoT security.