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

Arab Open University

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