Digital Connectivity – Social Impact: 51st Annual Convention by S. Subramanian, R. Nadarajan, Shrisha Rao, Shina Sheen

By S. Subramanian, R. Nadarajan, Shrisha Rao, Shina Sheen

This e-book constitutes the refereed lawsuits of the 51st Annual conference of the pc Society of India, CSI 2016, held in Coimbatore, India, in December 2016.

The 23 revised papers provided have been conscientiously reviewed and chosen from seventy four submissions. The subject of CSI 2016, electronic Connectivity - Social influence, has been chosen to focus on the significance of expertise in fixing social difficulties and thereby making a long-term effect on society. The papers are equipped in topical sections on info technology; computational intelligence; community computing; IT for society.

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Additional info for Digital Connectivity – Social Impact: 51st Annual Convention of the Computer Society of India, CSI 2016, Coimbatore, India, December 8-9, 2016, Proceedings

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7. Normal (a–d) PE image files (e–h) Malware detected image by proposed algorithm (i–l) Detected results superimposed on original PE files 52 E. Arul and V. Manikandan Fig. 8. Malware (a–d) PE image files (e–h) Malware detected image by proposed algorithm (i–l) Detected results superimposed on original PE files Malware Detection Using HSA 53 Fig. 9. FROC curve of proposed HSP for malware detection Table 2. Comparison of true positive ratio’s of various detection methods with proposed HSP Malware family No.

5 concludes the work and discuss its future scope. 2 Literature Survey The challenges being thrown to the modern world by malicious softwares (malware) and need to counteract them are becoming increasingly imminent. This is true in spite of the great improvements in the efficacy of procedures of malware propagation detection, analysis and updating, the bases of signatures and detection rules. The focus of this problem is to look for more reliable heuristic detection methods. These methods aim at recognizing of new malicious programs which cannot be detected by using traditional signature- and rule-based detection techniques which are oriented to search for concrete malware samples and families.

Pffiffiffiffiffiffi xi;j ð10Þ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðyi;j À yi þ 1;j þ 1 Þ2 þ ðyi þ 1;j þ yi;j þ 1 Þ2 ð11Þ yi;j ¼ zi;j ¼ Here x is pixel’s initial intensity value, z is the derivative that is computed and i; j represent the pixels location within the image. After the above operations the changes in intensity will be highlighted in a diagonal direction. The kernel used is very small and simple and contains only integers. Hence computation is very easy. A major drawback of the algorithm is that it is affected greatly by noise [6, 9].

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