Title

The Derivation And Use Of A Scalable Model For Network Attack Identification And Path Prediction

Keywords

Attacks; Defense; Exploits; Forecasting; Networks

Abstract

The rapid growth of the Internet has triggered an explosion in the number of applications that leverage its capabilities. Unfortunately, many are designed to burden or destroy the capabilities of their peers and the network's infrastructure. Hence, considerable effort has been focused on detecting and predicting the security breaches they propagate. However, the enormity of the Internet poses a formidable challenge to analyzing such attacks using scalable models. Furthermore, the lack of complete information on network vulnerabilities makes forecasting the systems that may be exploited by such applications in the future very hard. This paper presents a technique for deriving a scalable model for representing network attacks, and its application to identify actual attacks with greater certainty amongst false positives and false negatives. It also presents a method to forecast the propagation of security failures proliferated by an attack over time and its likely targets in the future. © 2008 Academy Publisher.

Publication Date

1-1-2008

Publication Title

Journal of Networks

Volume

3

Issue

4

Number of Pages

64-71

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.4304/jnw.3.4.64-71

Socpus ID

78651556193 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/78651556193

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