A monograph that comprises work on network-based Intrusion Detection (ID) that is grounded in visualisation and hybrid Artificial Intelligence (AI). It combines different AI paradigms to visualise network traffic for ID at packet level. Editor(s): Herrero, Alvaro; Corchado Rodriguez, Emilio S. Series: Studies in Computational Intelligence. Num Pages: 155 pages, biography. BIC Classification: TBC; UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 15. Weight in Grams: 432. . 2011. 2011th Edition. hardcover. . . . . Books ship from the US and Ireland.

Bestandsnummer des Verk�ufers V9783642182983

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Bibliografische Details

Titel: Mobile Hybrid Intrusion Detection
Verlag: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Erscheinungsjahr: 2011
Sprache: Englisch
ISBN-10: 3642182984
ISBN-13: 9783642182983
Einband: Hardcover
Zustand: New

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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.

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