Intelligent system for worm detection
Joint Authors
Subuh, Tariq
Faraj, Ibrahim A.
Shouman, Mohammed A.
al-Fiqqi, Hibah Z.
Source
International Arab Journal of E-Technology
Issue
Vol. 1, Issue 1 (31 Jan. 2009)10 p.
Publisher
Publication Date
2009-01-31
Country of Publication
Jordan
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
Worms are on the top of malware threats attacking computer system although of the evolution of worms detection techniques.
Early detection of unknown worms is still a problem.
This paper produce a method for detecting unknown worms based on local victim information.
The proposed system uses Artificial Neural Network (ANN) for classifying worm/ nonworm traffic and predicting the percentage of infection in the infected network.
This prediction can be used to support decision making process for network administrator to respond quickly to worm propagation in an accurate procedure
American Psychological Association (APA)
Faraj, Ibrahim A.& Shouman, Mohammed A.& Subuh, Tariq& al-Fiqqi, Hibah Z.. 2009. Intelligent system for worm detection. International Arab Journal of E-Technology،Vol. 1, no. 1.
https://search.emarefa.net/detail/BIM-38645
Modern Language Association (MLA)
Faraj, Ibrahim A.…[et al.]. Intelligent system for worm detection. International Arab Journal of E-Technology Vol. 1, no. 1 (Jan. 2009).
https://search.emarefa.net/detail/BIM-38645
American Medical Association (AMA)
Faraj, Ibrahim A.& Shouman, Mohammed A.& Subuh, Tariq& al-Fiqqi, Hibah Z.. Intelligent system for worm detection. International Arab Journal of E-Technology. 2009. Vol. 1, no. 1.
https://search.emarefa.net/detail/BIM-38645
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-38645