Network security surveillance aid using intelligent visualization for knowledge extraction and decision making

dc.contributor.author	Ξυδάς, Ιωάννης	el
dc.date.accessioned	2015-05-08T09:24:30Z
dc.date.issued	2015-05-08
dc.identifier.uri	http://hdl.handle.net/11400/9933
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://link.springer.com/bookseries/7092	en
dc.subject	Visual analytics
dc.subject	Web Visualization
dc.subject	Web Intrusion Detection
dc.subject	Evolutionary Artificial Neural Networks
dc.subject	Network Security
dc.subject	Surveillance Aid
dc.subject	Οπτική αναλυτική
dc.subject	Απεικόνιση δεδομένων διαδικτύου
dc.subject	Ανίχνευση διαδικτυακής εισβολής
dc.subject	Εξελικτικά Τεχνητά Νευρωνικά Δίκτυα
dc.subject	Ασφάλεια δικτύου
dc.subject	Ενίσχυση επιτήρησης
dc.title	Network security surveillance aid using intelligent visualization for knowledge extraction and decision making	en
heal.type	bookChapter
heal.classification	Technology
heal.classification	Computer science
heal.classification	Τεχνολογία
heal.classification	Πληροφορική
heal.classificationURI	http://zbw.eu/stw/descriptor/10470-6
heal.classificationURI	http://skos.um.es/unescothes/C00750
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Πληροφορική
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh2007004134
heal.identifier.secondary	DOI: 10.1007/978-3-540-92902-4_7
heal.identifier.secondary	Print ISBN: 978-3-540-92901-7
heal.identifier.secondary	Online ISBN: 978-3-540-92902-4
heal.dateAvailable	10000-01-01
heal.language	en
heal.access	forever
heal.recordProvider	Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Πληροφορικής Τ.Ε.	el
heal.publicationDate	2009
heal.bibliographicCitation	Xydas, I. (2009) Network security surveillance aid using intelligent visualization for knowledge extraction and decision making. In: Miaoulis, G. and Plemenos, D. (eds) "Intelligent Scene Modelling Information Systems". Berlin: Springer Berlin Heidelberg, p. 185-214. Available from: http://link.springer.com/chapter/10.1007%2F978-3-540-92902-4_7 [Accessed: 08/05/2015].	en
heal.abstract	Web sites are likely to be regularly scanned and attacked by both automated and manual means. Intrusion Detection Systems (IDS) assist security analysts by automatically identifying potential attacks from network activity and produce alerts describing the details of these intrusions. However, IDS have problems, such as false positives, operational issues in high-speed environments and the difficulty of detecting unknown threats. Much of ID research has focused on improving the accuracy and operation of IDSs but surprisingly there has been very little research into supporting the security analysts’ intrusion detection tasks. Lately, security analysts face an increasing workload as their networks expand and attacks become more frequent. In this chapter we describe an ongoing surveillance prototype system which offers a visual aid to the web security analyst by monitoring and exploring 3D graphs. The system offers a visual surveillance of the network activity on a web server for both normal and anomalous or malicious activity. Colours are used on the 3D graphics to indicate different categories of web attacks and the analyst has the ability to navigate into the web requests, of either normal or malicious traffic. The combination of interactive visualization and machine Intelligence facilitates the detection of flaws and intrusions in network security, the discovery of unknown threats and helps the analytical reasoning and the decision making process.	en
heal.publisher	Springer Berlin Heidelberg	en
heal.fullTextAvailability	false
heal.bookName	Intelligent Scene Modelling Information Systems	en