Analysis and visualization of large complex attack graphs for networks security

Hongda Chen; Genshe Chen; Erik Blasch; Martin Kruger; Irma Sityar

doi:10.1117/12.720035

9 April 2007 Analysis and visualization of large complex attack graphs for networks security

Hongda Chen, Genshe Chen, Erik Blasch, Martin Kruger, Irma Sityar

Proceedings Volume 6570, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2007; 657004 (2007) https://doi.org/10.1117/12.720035
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

In this paper, we have proposed a comprehensive and innovative approach for analysis and visualization of large complex multi-step cyber attack graphs. As an automated tool for cyber attack detection, prediction, and visualization, the newly proposed method transforms large quantities of network security data into real-time actionable intelligence, which can be used to (1) provide guidance on network hardening to prevent attacks, (2) perform real-time attack event correlation during active attacks, and (3) formulate post-attack responses. We show that it is possible to visualize the complex graphs, including all possible network attack paths while still keeping complexity manageable. The proposed analysis and visualization tool provides an efficient and effective solution for predicting potential attacks upon observed intrusion evidence, as well as interactive multi-resolution views such that an analyst can first obtain high-level overviews quickly, and then drill down to specific details.

Citation Download Citation

Hongda Chen, Genshe Chen, Erik Blasch, Martin Kruger, and Irma Sityar "Analysis and visualization of large complex attack graphs for networks security", Proc. SPIE 6570, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2007, 657004 (9 April 2007); https://doi.org/10.1117/12.720035

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available