A Hybrid Algorithm using Neural Network and Artificial Bee Colony for Cyber Security Threats
Abhishek Kajal1, Sunil Kumar Nandal2
1Abhishek Kajal, Assistant Professor, Department of Computer Science and Engineering, Guru Jambheshwar University of Science and Technology (GJUS&T), Hisar, Haryana.
2Dr. Sunil Kumar Nandal, Assistant Professor, Department of Computer Science and Engineering, Guru Jambheshwar University of Science and Technology (GJUS&T), Hisar, Haryana.
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 1-6 | Volume-8 Issue-12, October 2019. | Retrieval Number: L24781081219/2019©BEIESP | DOI: 10.35940/ijitee.L2478.1081219
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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: With the increasing literacy rate, the crowd over internet is increasing dramatically and so as the internet threats. Now these days, even kids below 10 are aware of what a virus is and how easily a virus can be created. This is a major problem for the data and stock companies who keep their entire data online or at any server which is traceable. This paper deals with some of the most malicious attacks of cyber world and they takes a little effort to be applied from the attacker side but a lot of effort to even detect it. This paper also focuses on some of the modern world prevention architectures like usage of Artificial Intelligence (Neural Networks) and Swarm Intelligence (Artificial Bee Colony [ABC]). This paper has evaluated the effectiveness of the prevention algorithm through Quality of Service parameters.
Keywords: Artificial Bee Colony, Network Security, Neural Networks, Prevention Mechanism, Threats.
Scope of the Article: Algorithm Engineering