TY - BOOK ID - 8433062 TI - Mobile hybrid intrusion detection : the MOVICAB-IDS system AU - Herrero, Alvaro. AU - Corchado, Emilio. PY - 2011 SN - 3642182984 3642182992 PB - Berlin : Springer, DB - UniCat KW - Electrical & Computer Engineering KW - Engineering & Applied Sciences KW - Telecommunications KW - Computer Science KW - Computer networks KW - Artificial intelligence. KW - Security measures. KW - AI (Artificial intelligence) KW - Artificial thinking KW - Electronic brains KW - Intellectronics KW - Intelligence, Artificial KW - Intelligent machines KW - Machine intelligence KW - Thinking, Artificial KW - Computer network security KW - Network security, Computer KW - Security of computer networks KW - Engineering. KW - Computational intelligence. KW - Computational Intelligence. KW - Artificial Intelligence (incl. Robotics). KW - Bionics KW - Cognitive science KW - Digital computer simulation KW - Electronic data processing KW - Logic machines KW - Machine theory KW - Self-organizing systems KW - Simulation methods KW - Fifth generation computers KW - Neural computers KW - Intelligence, Computational KW - Artificial intelligence KW - Soft computing KW - Construction KW - Industrial arts KW - Technology KW - Computer security KW - Artificial Intelligence. UR - https://www.unicat.be/uniCat?func=search&query=sysid:8433062 AB - 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. ER -