Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis

Main Article Content

Abbas M. Al-Bakri
Hussein L. Hussein

Abstract

 This paper argues the accuracy of behavior based detection systems, in which the Application Programming Interfaces (API) calls are analyzed and monitored. The work identifies the problems that affecting the accuracy of such detection models. The work was extracted (4744) API call through analyzing. The new approach provides an accurate discriminator and can reveal malicious API in PE malware up to 83.2%. Results of this work evaluated with Discriminant Analysis

Article Details

How to Cite
Al-Bakri, A. M., & Hussein, H. L. (2017). Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis. Ibn AL- Haitham Journal For Pure and Applied Sciences, 27(3), 556–565. Retrieved from https://jih.uobaghdad.edu.iq/index.php/j/article/view/320
Section
computer