Using Hierarchical Temporal Memory for Detecting Anomalous Network Activity

Bonhoff, Gerod M.

ISBN 10: 1288319959 / ISBN 13: 9781288319954

Published by BIBLIOSCHOLAR, 2012

About this Item

KlappentextrnrnThis research is motivated by the creation of intelligently autonomous cybercraft to reside in the intangible environment of cyberspace and maintain domain superiority. Specifically, this paper offers 7 challenges to the developme.

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Bibliographic Details

• Title: Using Hierarchical Temporal Memory for Detecting Anomalous Network Activity
• Publisher: BIBLIOSCHOLAR
• Publication Date: 2012
• Language: English
• ISBN 10: 1288319959
• ISBN 13: 9781288319954
• Binding: Soft cover
• Condition: New

About this title

Synopsis

This research is motivated by the creation of intelligently autonomous cybercraft to reside in the intangible environment of cyberspace and maintain domain superiority. Specifically, this paper offers 7 challenges to the development of such a cybercraft. The focus is analysis of the claims Hierarchical Temporal Memory (HTM). In particular, HTM theory claims to facilitate intelligence in machines via accurate predictions. It further claims to be able to make accurate predictions of unusual worlds, like cyberspace. The primary objective is to provide evidence that HTM facilitates accurate predictions of unusual worlds. The second objective is to lend evidence that prediction is a good indication of intelligence. A commercial implementation of HTM theory is tested as an anomaly detection system and its ability to define network traffic (a major aspect of cyberspace) as benign or malicious is evaluated. Through the course of testing the performance of this implementation is poor. An independent algorithm is developed from a variant understanding of HTM theory. This alternate algorithm is independent of cyberspace and developed solely (but also in a contrived abstract world) to lend credibility to the use of prediction as a method of testing intelligence.