International Journal of Advance Computational Engineering and Networking (IJACEN)
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Statistics report
Aug. 2020
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 87
Paper Published : 1231
No. of Authors : 3095
  Journal Paper

Paper Title
Characterizing Suspicious Images in Social Media Using EXIF Metadata

Online social networks (OSNs) have experienced tremendous growth in recent years and become a de facto portal for hundreds of millions of Internet users.Media sharing applications on internet contain a huge amount of pictures that need to be organized to facilitate browsing and retrieval. Images sent via online lately are becoming one of the main sources of attack to the client machine. Images are vulnerable to malicious embedded hidden data, most often because of the image contents are made attractive and code is hidden behind with executable. When those images are opened in some image viewer, they are vulnerable to execute the piece of code embedded in images, leaves behind the virus/worm on the machine. In the proposed system of image metadata extraction, there is provision of discarding the malicious images. This characterization is based upon the detailed skin tone analysis performed to affirm the presence of vulgar content in the images. We will try to show result experimentally that the proposed system performs well and fast in detecting vulgar images. The images should be reviewed whether they are malicious before they are opened so that the client can be prevented from being infected from malware.

Author - Sanket Ingale, Mayank Mehta

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| Published on 2014-01-18
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