z-logo
open-access-imgOpen Access
Anomaly Based Intrusion Detection and Artificial Intelligence
Author(s) -
Benot Morel
Publication year - 2011
Publication title -
intech ebooks
Language(s) - English
Resource type - Book series
DOI - 10.5772/14103
Subject(s) - anomaly detection , anomaly (physics) , intrusion detection system , intrusion , artificial intelligence , computer science , geology , physics , geochemistry , condensed matter physics
“The internet can be regarded as the most complex machine mankind ever built. We barely understand how it works, let alone how to secure it” [Schneier 2008]. The introduction of new technologies like the proliferation of new web applications or the increasing use of wireless, have exacerbated this fact. Cybersecurity, a spin-off of the phenomenal growth of the internet, has probably become the most complex threat to modern societies. The development of cybersecurity has been reactive and driven by the ingeniosity and imagination of cyberattackers. In the words of Carl Landwehr in IEEE security and Privacy (Landwehr 2008), "defense has consisted in “fixing the plumbing”. What we need is to put more Artificial Intelligence (AI) in cybersecurity". This is the theme of this chapter. Cyberspace is a rather brittle infrastructure, not designed to support what it does today, and on which more and more functionality is build. The fact that the internet is used for all sorts of critical activities at the level of individuals, firms, organizations and even at the level of nations has attracted all sorts of malicious activities. Cyber-attacks can take all sorts of forms. Some attacks like Denial of Service are easy to detect. The problem is what to do against them. For many other forms of attack, detection is a problem and sometimes the main problem. The art of cyber-attack never stops improving. The Conficker worm or malware (which was unleashed in Fall 2008 and is still infecting millions of computers worldwide two years later) ushered us in an era of higher sophistication. As far as detection goes, Conficker in a sense was not difficult to detect as it spreads generously and infected many honeypots. But as is the case for any other new malware, there are no existing tool which would automatically detect it and protect users. In the case of Conficker, the situation is worse in the sense that being a dll malware, direct detection and removal of the malware in compromise computers is problematic. One additional problem with Conficker is the sophistication of the code (which has been studied and reverse engineered ad nauseam) and of the malware itself (it had many functionality, was using encryption techniques to communicate (MD6) which had never been used before). It spreads generously worldwide using a variety of vectors, within networks, into a variety of military organizations, hospitals etc...). In fact the challenge became such that the security industry made the unprecedented move of joining forces in a group called the Conficker working group. The only indication that this approach met with some success is that even if the botnet that Conficker build involves millions of infected computers, that botnet does not seem to have been used into any attack, at least not yet....

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom