An Intrusion Detection System- Techniques and Algorithms of Machine and Deep Learning
Kavitha S1, Uma Maheswari N2, Venkatesh R3
1Kavitha S, Assistant Professor, Department of Computer Science and Engineering, Velammal College of Engineering and Technology, Madurai, (Tamil Nadu), India.
2Dr. Uma Maheswari N, Professor, Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul, (Tamil Nadu), India.
3Dr. Venkatesh R, Professor, Department of Information Technology, PSNA College of Engineering and Technology, Dindigul, (Tamil Nadu), India.
Manuscript received on July 10, 2020. | Revised Manuscript received on July 22, 2020. | Manuscript published on August 10, 2020. | PP: 370-376 | Volume-9 Issue-10, August 2020 | Retrieval Number: 100.1/ijitee.J75410891020 | DOI: 10.35940/ijitee.J7541.0891020
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Abstract: Computer networks are vital component for today’s development of science and technology, due to the emergence of limitless communication pattern and exponential count of network devices cyber security become crucial for this world to secure the most valuable data or information which is more vulnerable for attack by the intruders. New pattern of intrusion and attacks are created in everyday manner by potential intruders and they should be identified by efficient Intrusion Detection Systems (IDSs), also proper counter should be applied for. The paper surveys about the discussion of various machine /deep learning technology and algorithm related to Intrusion Detection System (IDSs) for the real time performance of the system. Finally the literature review investigated gives some open issues which will need to be considered for further research in the field of network security.
Keywords: Network Security, Intrusion Detection System, Signature-Based IDS, Anomaly-Based IDS, Machine Learning, Deep Learning, Artificial Neural Network, Deep Belief Network.
Scope of the Article: Machine Learning