Wednesday, February 28, 2007

Paper 3: Automated Discovery Of Mimicry Attacks

This papers describes an approach to checking that the models of model-based anomaly detection approachs really detect malicious system calls. Especially, the approach is aimed at discovering Mimicry Attacks, that is, calls that, for instance uses a buffer overflow, to invoke malicious system call sequences disguised as none-dangerous call sequences. Previously, the discovery of mimicry attacks were done manually.

A model-based anomaly detection approach uses a model describing the "normal" and allowed behavior of a monitored system. However, model-based anonaly detection can sometimes be cheated by the use of mimicry attacks that imitates "normal" behavior and thus these attacks are not detected.

In this paper they create a model of the Operating System (OS) monitored by a model-based anomaly detection system. Then they use the OS model to create a Push Down Automaton/Push Down System of the anomaly detection system. Thereafter a model checker, given a malicious goal for an attack (for instance, to create a new user account), can automatically either find a successful attack call sequence not detected by the detection system or prove that there are no attack call sequences for that goal not detected by the modeled automaton. This means that the reliability of this approach depends heavily on that the OS model is correct.

I think this was a quite interesting paper with nice results, though I am not that familiar with model checking and formal methods.

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Monday, February 26, 2007

Paper 2: Behavioral Distance Measurement Using Hidden Markov Models

In this paper, the authors describes how they to use a hidden markov model (HHM) to model the execution similarities between two process performing the same work. For instance, two Apache web servers running on two different platforms, Linux and Windows. The assumption is that the two process will not have the same vulnerabilities, and thus by measuring the behavioral distance between the two process, we can detect anomalies.

Much of the paper describes the HHM and whether the overhead is small enough to make the algorithm usefull.

Something missing is the significance of the results. For instance, when comparing another distance metric algorithm called an ED-based approach, the result is that the HHM-based approach is 6.32% faster, but nothing about the variance or significance. I would recommend any researcher to choose a good statistical test so results cannot be so easily questioned. A good online handbook for such tests can be found at the NIST/SEMATECH e-Handbook of Statistical Methods.

Paper 1: A Framework For The Application Of Association Rule Mining In Large Intrusion Detection Infrastructures

This paper is about using data mining in form of association rules to extract rules describing correlations between alarms from a large set of intrusion detection systems. The rules can then be used as basis for creating new rules to detect correlated intrusions.

Since the system mines for correlations between a huge amount of alarms it needs some form of data filtering. As filtering approach, the system uses graph algorithms with a graph where IP addresses are vertices and detected alarms are edges, drawn from source to destination IP addresses. Only connected components of the graph are used for mining.

Amongst the most interesting things in this article are the following:
  • The number of rules generated each day can be used to detect weired (anomalous) network activites.
  • This can also be done for each subnet of the network and thus find high risk networks.
A problem is though that the results they get are not able to repeat. I can imagine that this is often a problem in security research with sensitive data. Many of their results are like anecdotes that makes it hard to compare the results to other's work.

RAID 2006: Recent Advances in Intrusion Detection

I have just started a project about intrusion detection and prevention. As background reading I have a copy of the Proceedings of RAID 2006: Recent Advances in Intrusion Detection, 9th International Symposium. My plan is to initially start blogging about selected papers I am reading from the proceedings and then continue with papers from other sources.

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