State-of-the-Art Machine Learning and Deep Learning: Evolution of Intelligent Intrusion Detection System Against Wireless Network (Wi-Fi) Attacks in Internet of Things (IoT)
1Nivaashini M, Department of Computer Science & Engineering, Bannari Amman Institute of Technology, Erode (Tamil Nadu), India.
2Thangaraj P, Department of Computer Science & Engineering, Bannari Amman Institute of Technology, Erode (Tamil Nadu), India.
Manuscript received on 05 January 2019 | Revised Manuscript received on 13 January 2019 | Manuscript published on 30 January 2019 | PP: 118-130 | Volume-8 Issue-3, January 2019 | Retrieval Number: C2622018319/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: With the quick technical developments of devices and sensors, Wi-Fi have turned out to be a widespread technology for the Internet of Things (IoT). However, the benefit of wireless networks and IoT comes with a cost, which is mainly due to the concern of security and privacy. The distributed nature, multihop data forwarding, and open wireless medium are the factors that make wireless network highly vulnerable to security attacks at various levels. For more than two decades, Intrusion Detection Systems (IDSs) plays an important role in detecting and preventing such security attacks. Still, applying traditional IDS techniques to wireless network of IoT is difficult due to its particular characteristics such as constrained-resource devices, specific protocol stacks, and standards. Thus, a wide look at relating Intrusion Detection System (IDS) with machine learning procedures in scholastic world and in business field have been done commonly. Yet, massive information and complications to acquire data occurrences in machine-learning based IDS are sizzling challenges and correspondingly not sophisticated enough to handle persistently erratic wireless network conditions rising from the incredible network traffic evolution. Therefore, Deep learning, the modern revolution in the machine learning & intelligence zone, seems to be a feasible method in scheming Intellectual IDS. In this paper, a review on IDS research efforts by means of machine learning and deep learning practices in wireless networks of IoT has be offered along with the summary of upcoming research guidelines in IDS using deep learning procedures to overwhelm the limits of earlier typical machine learning based IDSs.
Keyword: Intrusion Detection System, Wireless Networks, Internet of Things, Machine Learning Techniques, Deep Learning Techniques.
Scope of the Article: Deep Learning