Viruses are designed to run helter-skelter through our computer and caused actual, intentional damage to the computer itself. This can be in the form of corrupting files on our computer, damaging our personal documents, photos, music track, and more to rendering the computer completely unusable. Viruses usually don't have an ulterior motive like spyware programs do, they are made to maliciously damage our computer and cause us problems. Like human viruses, computer viruses also replicate themselves, and spread by embedding into email attachments and other shared files. There are various detection techniques available and used by antivirus software to identify virus infected files and mark those files as infected and also try to clean them if possible. These techniques are successful to detect some specific category of viruses but may fail to detect other category of viruses. Some of the main categories of virus detection techniques are Static Signature Scanning Technique, Generic Signature Scanning Technique, Heuristic Analysis Technique and Integrity Checking Technique. But each of these techniques has its own limitations and the techniques fail to detect viruses with properties beyond the scope of the technique used. So, each antivirus software uses mixed set of techniques to detect virus infections in files. This paper discusses various types of virus threats and analyses various detection techniques in view of their limitations.
Virus, Virus History, Types of Virus, Life Cycle of Virus, Virus Detection Techniques, Static Signature Scanning Technique, Generic Signature Scanning Technique, Heuristic Analysis Technique and Integrity Checking Technique.
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|Published in :
||Volume 1 | Issue 6 | November-December - 2015
|Date of Publication
Cite This Article
Harjit Singh, "Computer Viruses - Analysis of Detection Techniques and their Limitations", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 6, pp.498-504, November-December-2015.
URL : http://ijsrset.com/IJSRSET151628.php