A SYSTEMATIC APPROACH TO STUDY THE SECURITY BEHAVIOR FOR DATA MINING
Mohammad Iquebal Akhter
Research scholar, Nawab Shah Alam khan College of Engineering and Technology, Hydrabad , IN
Dr. Gulam Ahamad
Research scholar, Nawab Shah Alam khan College of Engineering and Technology, Hydrabad , IN
Keywords: Data mining, Classification, Clustering, Privacy Preservation, Outlier Detection, Anomaly Detection
Abstract
While enabling individuals to elicit hidden knowledge on the one hand, data mining techniques pose many privacy threats on the other hand. Data mining technology has many uses in malware detection. Classification and clustering methods are one of the most common data mining techniques. In this paper, we propose a data mining taxonomy for detecting malware behavior. This article examined some of these issues and described in detail the application of various data mining techniques to provide security. The most effective use of data mining is intrusion detection. Various data mining techniques can be used to effectively detect and report intrusions in real time, in order to take the necessary precautions to prevent intruder attempts. This article discusses privacy protection, anomaly detection, and classification.
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