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

Name: Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis
Keywords: PE Malwares, Malicious API, ANN, Discriminant Analysis, Science, Q

descriptionPublicationkeyboard_double_arrow_right Article 01 Apr 2017 English Publisher:University of BaghdadJournal:Ibn Al-Haitham Journal for Pure and Applied Sciences (issn: 1609-4042,

Authors: Abbas M. Al-Bakri; Hussein L. Hussein;

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

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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

Keywords

PE Malwares, Malicious API, ANN, Discriminant Analysis, Science, Q

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