Mobile Hybrid Intrusion Detection: The MOVICAB-IDS System (Studies in Computational Intelligence, 334)

This monograph comprises work on network-based Intrusion Detection (ID) that is grounded in visualisation and hybrid Artificial Intelligence (AI) . It has led to the design of MOVICAB-IDS (MObile VIsualisation Connectionist Agent-Based IDS) , a novel Intrusion Detection System (IDS) , which is comprehensively described in this book.This novel IDS combines different AI paradigms to visualise network traffic for ID at packet level. It is based on a dynamic Multiagent System (MAS) , which integrates an unsupervised neural projection model and the Case-Based Reasoning (CBR) paradigm through the use of deliberative agents that are capable of learning and evolving with the environment.The proposed novel hybrid IDS provides security personnel with a synthetic, intuitive snapshot of network traffic and protocol interactions. This visualisation interface supports the straightforward detection of anomalous situations and their subsequent identification. The performance of MOVICAB-IDS was tested through a novel mutation-based testing method in different real domains which entailed several attacks and anomalous situations.