Share Email Print
cover

Proceedings Paper

From measurements to metrics: PCA-based indicators of cyber anomaly
Author(s): Farid Ahmed; Tommy Johnson; Sonia Tsui
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

We present a framework of the application of Principal Component Analysis (PCA) to automatically obtain meaningful metrics from intrusion detection measurements. In particular, we report the progress made in applying PCA to analyze the behavioral measurements of malware and provide some preliminary results in selecting dominant attributes from an arbitrary number of malware attributes. The results will be useful in formulating an optimal detection threshold in the principal component space, which can both validate and augment existing malware classifiers.

Paper Details

Date Published: 7 May 2012
PDF: 10 pages
Proc. SPIE 8408, Cyber Sensing 2012, 840806 (7 May 2012); doi: 10.1117/12.918165
Show Author Affiliations
Farid Ahmed, The Johns Hopkins Univ. Applied Physics Lab. (United States)
Tommy Johnson, The Johns Hopkins Univ. Applied Physics Lab. (United States)
Sonia Tsui, The Johns Hopkins Univ. Applied Physics Lab. (United States)


Published in SPIE Proceedings Vol. 8408:
Cyber Sensing 2012
Igor V. Ternovskiy; Peter Chin, Editor(s)

© SPIE. Terms of Use
Back to Top