Cyber Safety System by Implementing Integration of Expert Learning and Data Mining Concepts
Mrinal Paliwal
Mrinal Paliwal, Department of Computer Science and Engineering, Sanskriti University, (Uttar Pradesh), India.
Manuscript received on 05 October 2019 | Revised Manuscript received on 19 October 2019 | Manuscript Published on 26 December 2019 | PP: 155-158 | Volume-8 Issue-12S October 2019 | Retrieval Number: L104710812S19/2019©BEIESP | DOI: 10.35940/ijitee.L1047.10812S19
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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: The continuous growth in the rate of cyber-attacks in recent years uplifts the worry for the cyber security of industrial control systems. The current efforts of the cyber security system are depended on firewalls, data diodes and other basic methods for prevention of infringement. A cyber threat, intrusion or infringement detection system detects malicious or noxious activities by scanning a system and investigate digitally by employing “machine learning” and “data digging” techniques for handling dynamic and complex functioning of malicious assaults in computer systems and extracting essential information from an input data. In this research paper, the techniques we have used to complete this research may bring advancement in recognition rates, decrease the fault rate which also led to a decrease in the cost factor.
Keywords: Rundown phrases— Threat, Infringement, Cyber, Machine Learning, Data Digging.
Scope of the Article: Data Mining