DCA for Bot Detection

Abstract-- Ensuring the security of computers is a nontrivial task, with many techniques used by malicious users to compromise these systems. In recent years a new threat has emerged in the form of networks of hijacked zombie machines used to perform complex distributed attacks such as denial of service and to obtain sensitive data such as password information. These zombie machines are said to be infected with a'bot' - a malicious piece of software which is installed on a host machine and is controlled by a remote attacker, termed the'botmaster of a botnet'. In this work, we use the biologically inspired Dendritic Cell Algorithm (DCA) to detect the existence of a single bot on a compromised host machine. The DCA is an immune-inspired algorithm based on an abstract model of the behaviour of the dendritic cells of the human body. The basis of anomaly detection performed by the DCA is facilitated using the correlation of behavioural attributes such as keylogging and packet flooding behaviour. The results of the application of the DCA to the detection of a single bot show that the algorithm is a successful technique for the detection of such malicious software without responding to normally running programs. Computer systems and networks come under frequent attack from a diverse set of malicious programs and activity. Computer viruses posed a large problem in the late 1980's and computer worms were problematic in the 1990s through to the early 21st Century. While the detection of such worms and viruses is improving a new threat has emerged in the form of the botnet. Botnets are decentralised, distributed networks of subverted machines, controlled by a central commander, affectionately termed the'botmaster'. A single bot is a malicious piece of software which, when installed on an unsuspecting host, transforms host into a zombie machine.