Intelligent Perpetual Echo Attack Detection on User Datagram Protocol Port 7 Using Ant Colony Optimization

The escalating complexity of computer networks on a daily basis has increased the probability of malicious exploitation. Even a rare vulnerability in a single computer might compromise the network security of an entire organisation. Intrusion Detection Systems form an integral component of the mechanisms designed to prevent internet and data communication systems from such attacks. The attacks on the network comprise of information gathering and modification through unauthorized access to resources and denial of service to legitimate users. IDS play a key role in detecting the patterns of behaviour on the network that might be indicative of impending attacks. Majority of groundbreaking research on IDS is carried out on KDD'99 dataset and focuses on either all the attacks in the network or the attacks corresponding to TCP/IP protocol. This paper presents a step forward in this direction where the IDS model addresses a specific part of the network attacks commonly detected at port 7 in UDP. Port scans in UDP account for a sizable portion of the Internet traffic and comparatively little research characterizes security in UDP port scan activity. To meet the growing trend of attacks and other security challenges in the constantly evolving internet arena, this is paper presents a computationally intelligent intrusion detection mechanism using swarm intelligence paradigm, particularly ant colony optimisation, to analyze sample network traces in UDP port scans. This work aims at generating customised and efficient network intrusion detection systems using soft computing to increase general network security through specific network security.