Malware detection techniques using artificial immune system
Using artificial immune system techniques for malware detection has two major benefits. First, increasing the ability to come over some of the traditional detector’s drawbacks, like dealing with the new and polymorphic malware and the increased number of false alarms caused by wrong decision. Second...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Published: |
Springer-Verlag
2012
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/47171/ http://dx.doi.org/10.1007/978-94-007-2911-7_55 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Teknologi Malaysia |
| Summary: | Using artificial immune system techniques for malware detection has two major benefits. First, increasing the ability to come over some of the traditional detector’s drawbacks, like dealing with the new and polymorphic malware and the increased number of false alarms caused by wrong decision. Second take advantages of the capabilities to learn, adapt, self-tolerance and memories actions, which make it a good example that we can take for solving some major problems in many fields, including the problem of malware detection in computer security which suffering from the rapid increasing in the malware and the problem of false positive alarms. In this paper, we try to highlight the recent techniques applied in malware detection using the artificial immune system from two points of view: self–nonself theory, danger theory. |
|---|