Spyware Detection


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  • Product Description

Malware represents a significant problem that threatens the security of computer systems. Spyware is one of the recent types of malware that represents a serious threat to confidentiality. The traditional approaches using signature-based to detect spyware programs fails in detecting new and unknown spyware. Many of the malware detection techniques which work well in detecting malware are not investigated in terms of spyware detection. In this research, we investigate the spyware detection by using data mining techniques based on mining Application Programming Interface (API) calls. 2084 spyware and 1065 benign windows Portable Executable (PE) file samples were collected in order to create binary data set. API call statically extracted from binary file, then generate a set of features and features selection was performed, these features are then used to train a classifier. We evaluated a variety of classification algorithms. The accuracy and the area under ROC curve are used for the evaluation of classifier performance. The results show that we achieved an overall accuracy of 98.09% with an area under the ROC curve of 0.995.

Product Specifications
SKU :COC65570
AuthorFadel O. Shaban
Number of Pages92
Publishing Year2013-11-20T00:00:00.000
Edition1 st
Book TypeComputing & information technology
Country of ManufactureIndia
Product BrandLAP LAMBERT Academic Publishing
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-07-08 00:00:00
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