Please use this identifier to cite or link to this item:
http://ir.futminna.edu.ng:8080/jspui/handle/123456789/1960
Title: | Malware Detection, Supportive Software Agents and Its Classification Schemes |
Authors: | Adebayo, Olawale Surajudeen Mabayoje, Modina A. Mishra, Amit Osho, Oluwafemi |
Keywords: | Malware Malware Detection Malware Classification Malware Supportive Software Agents |
Issue Date: | 2012 |
Publisher: | International Journal of Network Security & Its Applications (IJNSA) |
Series/Report no.: | Volume 4;6 |
Abstract: | Over time, the task of curbing the emergence of malware and its dastard activities has been identified in terms of analysis, detection and containment of malware. Malware is a general term that is used to describe the category of malicious software that is part of security threats to the computer and internet system. It is a malignant program designed to hamper the effectiveness of a computer and internet system. This paper aims at identifying the malware as one of the most dreaded threats to an emerging computer and communication technology. The paper identified the category of malware, malware classification algorithms, malwares activities and ways of preventing and removing malware if it eventually infects system. The research also describes tools that classify malware dataset using a rule-based classification scheme and machine learning algorithms to detect the malicious program from normal program through pattern recognition |
URI: | http://repository.futminna.edu.ng:8080/jspui/handle/123456789/1960 |
Appears in Collections: | Cyber Security Science |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Malware detection.pdf | 144.5 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.