Machine Learning Techniques for Securing IoT Environment
Amit Sagu1, Nasib Singh Gill2

1Amit Sagu*, Research Scholar, Department of Computer Science & Applications, Maharshi Dayanand University, Rohtak, India.
2Nasib Singh Gill, Professor, Department of Computer Science & Applications, Maharshi Dayanad University, Rohtak, India.
Manuscript received on January 11, 2020. | Revised Manuscript received on January 21, 2020. | Manuscript published on February 10, 2020. | PP: 977-982 | Volume-9 Issue-4, February 2020. | Retrieval Number: D1209029420 /2020©BEIESP | DOI: 10.35940/ijitee.D1209.029420
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Abstract: IoT (Internet of Thing) is becoming ubiquitous day by day and making dumb devices smarter by enabling them to transfer the information over the network. IoT not confined to homes or in utilities but can be found in array of fields. IoT is rapidly making the world smarter by connecting physical to digital world and it is estimated that by 2024 more than 20 billion devices are likely to be connected. It brings opportunity but also brings numerous kind of risks. The worry is how we to keep billions of devices secure and what to ensure the security of networks these run on. The present paper focused on all the issues concerning about securing IoT environment and how machine learning techniques may help to address these security issues. The paper also discusses the proposed approaches, parameters, characteristic of techniques and explores which technique could be more effective. 
Keywords: IoT, Security Challenges, Machine learning
Scope of the Article: Machine learning