Intelligent and Effective Intrusion Detection System using Machine Learning Algorithm
Bhakti Nandurdikar1, Rupesh Mahajan2
1Bhakti Nandurdikar*, Dr.D.Y.Patil Institute of Technology, Pune. India.
2Rupesh Mahajan, Dr.D.Y.Patil Institute of Technology, Pune. India.
Manuscript received on July 12, 2020. | Revised Manuscript received on July 20, 2020. | Manuscript published on August 30, 2020. | PP: 237-240 | Volume-9 Issue-6, August 2020. | Retrieval Number: F1231089620/2020©BEIESP | DOI: 10.35940/ijeat.F1231.089620
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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: Intrusion Detection System observes the network traffic and identifies the attack and also inform the admin to corrective action. Powerful Intrusion Detection system is required for detection to various modern attack. There is need of efficient Intrusion Detection system .The focus of IDS research is the application of machine Learning and Deep Learning techniques. Projected work is combination of Deep Learning Technique in which Non Symmetric Deep Auto Encoder and Machine Learning Algorithm, Support Vector Machine Classifier is used to develop the Model. Stack power of the Non symmetric Deep Auto Encoder and Quickness with exactness of the SVM makes the Model very efficient. This Model not only improves the accuracy value but also improve recall and precision. It also cause the reduction of training time .To evaluate the performance of the Model and do the analysis the special Data set which are used are KDD CUP and NSL KDD Dataset.
Keywords: Auto-encoders. Deep and Machine Learning, intrusion detection, Network security.