Reduction of False Positive Intrusions by using Neural Nets

Paper Reduction of False Positive Intrusions by using Neural Nets, which I worked on with colleagues, is now available at IEEE Digital Library.


The main idea of this paper is to propose a new solution for a Wireless Intrusion Detection Prevention System (WIDPS). The proposed WIDPS has a high degree of autonomy in tracking suspicious activity and detecting positive intrusions. Our focus was the reduction of detected false positive intrusion by implementing adaptive self-learning neural net in the system. Once it is fully developed and tested, this WIDPS would enable real-time response against threats, even to zero-day attacks.

Remark: Subscription to IEEE Digital Library required to download full paper in PDF format.

Share this... Tweet about this on TwitterShare on LinkedInShare on FacebookShare on Google+Email this to someone

3 Responses

  1. Any chance of posting it publicly (or at least emailing it to me :-)) I am really curious to see it…

  2. I have to see details of IEEE Copyright form and find out what I am allowed to do before I do public posting or anything.

Leave a Reply