IDS mailing list archives

Re: How do behavioral/anomaly detection systems learn?


From: david maynor <david.maynor () oit gatech edu>
Date: Thu, 05 Feb 2004 09:44:28 -0500

Depending on the system it can widely vary. Most of these system create
a baseline of network traffic and flag on behavior that widely varies
from the baseline. This is not the only method, many systems include
protocol analysis and rfc compliance. An example of protocol analysis is
checking for encrypted tunnels over port 80 by the amount of traffic
transfered with out valid HTTP traffic. 

Your question is more about how they learn. There are two answers to
this and neither of them are pretty. One is manual. This means after a
certain number of false positives (like a user running an application
that was present during the baseline) you would add the traffic pattern
to the profile by hand. As everyone knows this is not effective for
anything larger than a class C. The second way is through an automated
process where a threshold and a time value are set and after a certain
amount of time the abnormal traffic behavior becomes part of the
offending hosts profile. This means in the future similar traffic will
not cause and alarm. There are some provisions in the systems to alert
on know bad traffic patterns like fileswapping but you the effectiveness
of the device is limited at this point. 

There are attacks you can do against such a system like a "low slow"
attack where someone could do whatever they as long as it is rate
limited. Another example is someone who spends the time to "teach" the
system bad habits. 

Simple thing like this are why such systems should be used in
conjunction with signature based systems. The ideal product would have a
hybrid of both. 


On Thu, 2004-02-05 at 01:18, Sasha Romanosky wrote:
Greetings, 

In regards to "behavioral" or "anomaly" detection systems vs. pure
signature-based detection systems, I'm trying to understand how these
behavioral technologies differentiate "good" traffic from "bad" traffic.
I don't want to get into which is better, because they both have their
place, of course. What I'm trying to understand is how these behavioral
systems work, or "learn". 

I have seen that this technique is not unique to intrusion detection
systems, but also appears in application firewalls (e.g. Teros) and
email virus scanners (e.g. using bayesian filtering). 

With some products, I see that you configure them with specific rules,
tailored to your particular environment, and with other products, you
just point it to the network and it creates a profile all by itself. 

Does this simply amount to another form of signature system, just with
more intelligent signatures? Or is it more complex than this?.

Any references (whitepapers, archives, sites, etc) explaining this
learning would be most appreciated.


Cheers,
Sasha Romanosky


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