Title of article
Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis
Author/Authors
al-bakri, abbas m. university of kuffa - college of computer and mathematics, Iraq , hussein, hussein l. universityof baghdad - college of eduucationfor pure science(ibn al-haitham) - department of computer science, Iraq
Pages
10
From page
556
To page
565
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
Discriminant Analysis , ANN , Malicious API , PE Malwares
Journal title
Ibn Alhaitham Journal For Pure and Applied Science
Serial Year
2014
Journal title
Ibn Alhaitham Journal For Pure and Applied Science
Record number
2602448
Link To Document