By Topic

Taichi: An Open Intrusion Automatic Response System Based on Plugin

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Hong Han ; Coll. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China ; Xian-Liang Lu ; Li-Yong Ren ; Bo Chen

For most current intrusion detection systems, the capability to counterstrike network intrusion is limited. And the automatic protection of intranet is extremely difficult. In this paper, we present a system: TAICHI which combines heterogeneous intrusion detection systems with improved distributed firewall system (IDFS) to automatically detect and prevent intrusion originated from intranet or Internet. TAICHI can manage heterogeneous IDSs (intrusion detection systems) and firewalls with plugin, which makes it evolved easily to employ new detection technology and to integrate legacy firewall in an organization. ECA (extended common alert) in TAICHI can analyze alerts from heterogeneous IDSs. The system employs IDFS as a response subsystem, which could easily block attack originated from intranet or Internet. To configure heterogeneous firewalls efficiently, extended meta-firewall-rule configuration (EMFRC) was presented, which can not only configure firewall in a unified template, but also set special options of rules of different type with the same template. Due to EMFRC and IDFS, TAICHI makes the optimized strategy automatically to block intrusion from different network topology

Published in:

Machine Learning and Cybernetics, 2006 International Conference on

Date of Conference:

13-16 Aug. 2006