Development of a Threat Detection System for Network Attacks
G. Krishna Kishore1, Suresh Babu Dasari2, S. Ravi Kishan3

1G. Krishna Kishore, Department of Computer Science and Engineering, V.R. Siddhartha Engineering College, Vijayawada. (Andhra Pradesh), India.
2Suresh Babu Dasari , Department of Computer Science and Engineering, V.R. Siddhartha Engineering College, Vijayawada. (Andhra Pradesh), India.
3S. Ravi Kishan, Department of Computer Science and Engineering, V.R. Siddhartha Engineering College, Vijayawada. (Andhra Pradesh), India.

Manuscript received on 13 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 205-209 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2187037619/19©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: In today’s world the structure and dynamic interactions in the large network systems has become substantially complex. The threats and security attacks are currently spread everywhere and are tend to increase significantly in the future with the Internet of Things (IoT). The late detection of security threats causes a significant increase in the risk of irreparable damages, disabling any defense attempt. In this new era of security, information security professionals must deliver a very effective, real-time defense that can predict inherent threats to all the critical assets. All attacks will leave detectable traces, even though most of them will be complex and very hard to analyze. Threat monitoring systems, must have the capacity to observe activities in big data collected from networks and detect the threats. In order to provide the most secured network environment and network traffic monitoring threat detection systems must handle the real-time data. An accurate and reliable TDS will be automated that will be able to improve the traditional methods in order to fulfill the goals quickly and detect malicious activity and act accordingly. We focus on a robust classification method that includes an efficient SVM classifier will be used to handle network security concerning big network traffic.
Keywords: Threat Detection System (TDS), Network Attacks, Support Vector Machine (SVM), Network Security

Scope of the Article: Mobile App Design and Development