A Comparison study of Computer Virus and Detection Techniques

Authors(1) :-Soumen Chakraborty

The virus is a kind of program which seriously infects the system, large organizations nowadays have big data to maintain which are spread to various locations in the world. As a result, security is a major issue for all companies nowadays. The data is the ultimate asset for any people nowadays. Which needs various precautions to maintain to keep safe those assets. As there is growing the popularity of various kind of virus like malware,trojan,hackers,adware it is really becoming a challenge to keep the system secure.With the growing popularity of internet in our daily lives, the risk of various kind of threats is also increasing day by day. There is various kind of virus also various kind of mechanism to catch that virus which needs proper analysis.In this paper, there is a small survey of various kind of virus detection methods along with their consequences it does to the system.That will help to understand the merits and demerits of each virus after the survey.At the end, there is a conclusion and some information on what can be done to keep away from the virus in a large virtual world.

Authors and Affiliations

Soumen Chakraborty
Department of Information Technology, MCKV Institute of Engineering, MAKAUT, West Bengal, India

Virus, Virus Detection, Signature-Based Virus Detection, Anomaly-Based Detection, Trojan

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Publication Details

Published in : Volume 2 | Issue 1 | January-February 2017
Date of Publication : 2017-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 236-240
Manuscript Number : CSEIT172132
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Soumen Chakraborty, "A Comparison study of Computer Virus and Detection Techniques", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 1, pp.236-240, January-February-2017.
Journal URL : http://ijsrcseit.com/CSEIT172132

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