Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm
Joint Authors
Zeng, Yong
Liu, Dacheng
Lei, Zhou
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-24
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms.
To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE).
First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect.
Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting.
Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy.
This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning.
The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously.
American Psychological Association (APA)
Zeng, Yong& Liu, Dacheng& Lei, Zhou. 2014. Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1049747
Modern Language Association (MLA)
Zeng, Yong…[et al.]. Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm. The Scientific World Journal No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1049747
American Medical Association (AMA)
Zeng, Yong& Liu, Dacheng& Lei, Zhou. Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1049747
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049747