Modelling the Network Behaviour of Malware To Block Malicious Patterns

Garcia, S. (2015). Modelling the Network Behaviour of Malware To Block Malicious Patterns . The Stratosphere Project : A Behavioural IPS. Virus Bulletin Conference. doi: 10.13140/RG.2.1.3784.7765

Abstract

Current malware traffic detection solutions work mostly by using static fingerprints, white and black lists and crowd-sourced threat intelligence analytics. These methods are useful for detecting known malware in real time, but are insufficient for detecting unknown malicious trends and attacks. Our proposed complementary solution is to analyse the inherent patterns of malware actions in the network by means of machine learning algorithms. In particular, we use Markov chains-based algorithms to find network patterns that are independent of static features, such as IP addresses or payloads. These patterns are used to build behavioural models of malware actions that are later used to detect similar traffic in the network. All these models and detection algorithms have been used to create a free software intrusion prevention system called Stratosphere IPS, which has been thoroughly tested with normal and malware traffic. The IPS is able to detect new network patterns that are similar to known malicious behaviours. The Stratosphere IPS tool will be used to show how behavioural models can detect real malware traffic.

Characteristics of the botnet captures. (CF_ Click Fraud, PS_ Port Scan, US_ Compiled and controlled by us.).png
This presentation by Sebastian Garcia (CTU University, Prague) was delivered at VB2015 in Prague, Czech Republic. Current malware traffic detection solutions...