Authors : Nawfal Turki Obeis and Wesam Bhaya
Abstract: Malicious is the term used to illustrate any code in any part of a software system that is expected to bring about undesired impacts, security breaks or harm to a system. Malicious programming is outlined with a hurtful intent. Recently, malicious detectors attempt to distinguish unwanted codes by checking Application Programming Interface (API) calls using data mining techniques and/or different methods. Matching the API call utilizing data mining strategies can be utilized as a part of malicious detection systems, for example, frequent pattern, clustering, etc. In this study, a review of malicious detection system based on API calls and data mining strategies are taking into account. Each malicious sample is represented as a data of API calls to the data mining techniques. After transforming the sample that input as a simplified data based on data mining techniques, data mining matching calculations are utilized to similarity between the data tested sample and malicious API call tested samples placed in a database. In this study, a review of utilization of various data mining methods for the detection of malicious program.
Nawfal Turki Obeis and Wesam Bhaya, 2016. Review of Data Mining Techniques for Malicious Detection. Research Journal of Applied Sciences, 11: 942-947.