International Journal of Communication Networks and Information Security ISSN: 2073-607X, 2076-0930 Volume 14 Issue 02 Year 2022 Page 124:141 _____________________________________________________________________________________________________________________________ ____________________________ Available online at: https://ijcnis.org 124 Security Enhancement by Identifying Attacks Using Machine Learning for 5G Network 1 Dr. Hitesh Keserwani, 2 Dr. Himanshu Rastogi, 3 Ardhariksa Zukhruf Kurniullah, 4 Sushil Kumar Janardan, 5 Dr. Ramakrishnan Raman, 6 Mr. Vinod Motiram Rathod, 7* Ankur Gupta 1 Assistant Professor, Amity Business School, Amity University, Lucknow, Uttar Pradesh, India hkesarwani@lko.amity.edu 2 Associate Professor, Amity Business School, Amity University, Lucknow, Uttar Pradesh, India hrastogi@lko.amity.edu 3 Faculty of Communications Science, Universitas Mercu Buana, Jakarta, Indonesia ardhariksa.zukhruf@mercubuana.ac.id 4 Assistant Professor, Department of Computer Science and Engineering, Rungta College of Engineering and Technology Bhilai, Rungta Educational Campus, Kohka-Kurud Road, Bhilai - 490024, Chhattisgarh, India ssushil30@gmail.com 5 Professor and Director, Symbiosis Institute of Business Management, Pune & Symbiosis International (Deemed University), Pune, Maharashtra, India raman06@yahoo.com 6 Assistant Professor, Bharati Vidyapeeth Deemed University, Department of Engineering and Technology, Navi Mumbai, Maharashtra, India vinod.rathod@bvucoep.edu.in 7 Assistant Professor, Department of Computer Science and Engineering, Vaish College of Engineering, Rohtak- 124001, Haryana, India ankurdujana@gmail.com Article History Received: 11 May 2022 Revised: 26 July 2022 Accepted: 28 August 2022 Abstract Need of security enhancement for 5G network has been increased in last decade. Data transmitted over network need to be secure from external attacks. Thus there is need to enhance the security during data transmission over 5G network. There remains different security system that focus on identification of attacks. In order to identify attack different machine learning mechanism are considered. But the issue with existing research work is limited security and performance issue. There remains need to enhance security of 5G network. To achieve this objective hybrid mechanism are introduced. Different treats such as Denial-of-Service, Denial-of-Detection, Unfair use or resources are classified using enhanced machine learning approach. Proposed work has make use of LSTM model to improve accuracy during decision making and classification of attack of 5G network.