IJCATR Volume 7 Issue 3

Malware Family Detection Approach using Image Processing Techniques: Visualization Technique

Poonam Parmuval , Mosin Hasan , Samip Patel
10.7753/IJCATR0703.1004
keywords : Malwares, Malware Family, Malware Visualization, Malware Detection, Malware family classification

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The risk of malicious software has increased a lot since last decade as the use of internet has increased drastically. According to Avast Test report, 22,000 to 25,000 new malware have been reported every day. Even though huge malwares having different structures are introduced every day, their nature of working is almost similar to old malwares. The malwares with the similar functionalities are considered to be the member of the same family. Classification and detection of malware family are important to design its signature of anti-malware software. In this article, we represent the concise study carried out on detecting various malware family. This paper mainly focus on visualization technique for classifying malware family. Visualization technique uses image processing approaches to classify the malwares. The malware executable binary files are transformed into image and this images are used to detect the family of malware.
@artical{p732018ijcatr07031004,
Title = "Malware Family Detection Approach using Image Processing Techniques: Visualization Technique",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "7",
Issue ="3",
Pages ="129 - 132",
Year = "2018",
Authors ="Poonam Parmuval , Mosin Hasan , Samip Patel"}
  • Paper gives study of different malware classification Techniques
  • Classification is based on Visualization Technique
  • Malware Images are used for classification instead of malware binary
  • Different feature extraction of malware image.