Spyware Detection Using Data Mining
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 3
Abstract
The systems connected to the network are vulnerable to many malicious programs which threatens the confidentiality, integrity and availability of a system. Many malicious programs such as viruses, worms, trojan horses, adware, scareware exists. A new malicious program has gained momentum known as spyware. Traditional techniques such as Signature-based Detection and Heuristicbased Detection have not performed well in detecting Spyware. Based on the recent studies it has been proven that data mining techniques yield better results than these traditional techniques. This paper presents detection of spyware using data mining approach. Here binary feature extraction takes place from executable files, which is then followed by feature reduction process so that it can be used as training set to generate classifiers. Hence, the generated classifiers classify new and previously unseen binaries as benign files or spywares.
Authors and Affiliations
Karishma Pandey, Madhura Naik, Junaid Qamar, Mahendra Patil
Keywords
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