Using visual analytics for web intrusion detection

dc.contributor.author	Ξύδας, Ιωάννης	el
dc.contributor.author	Μιαούλης, Γεώργιος	el
dc.contributor.author	Bonnefoi, Pierre-François	en
dc.contributor.author	Πλεμμένος, Δημήτρης	el
dc.contributor.author	Ghazanfarpour, Djamchid	en
dc.date.accessioned	2015-02-11T23:28:51Z
dc.date.available	2015-02-11T23:28:51Z
dc.date.issued	2015-02-12
dc.identifier.uri	http://hdl.handle.net/11400/6078
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://e-jst.teiath.gr/	en
dc.subject	Web Visual Analytics
dc.subject	Web Attacks Visualization
dc.subject	Web Intrusion Detection
dc.subject	Evolutionary Artificial Neural Networks
dc.subject	Network Security
dc.subject	Surveillance Aid
dc.subject	Εξελιγμένα Τεχνητά Νευρωνικά Δίκτυα
dc.subject	Ασφάλεια Δικτύων
dc.subject	Ενίσχυση επιτήρησης
dc.title	Using visual analytics for web intrusion detection	en
heal.type	journalArticle
heal.classification	Science
heal.classification	Mathematics
heal.classification	Επιστήμες
heal.classification	Μαθηματικά
heal.classificationURI	http://zbw.eu/stw/descriptor/15685-2
heal.classificationURI	http://zbw.eu/stw/thsys/70269
heal.classificationURI	N/A-Επιστήμες
heal.classificationURI	N/A-Μαθηματικά
heal.language	en
heal.access	free
heal.publicationDate	2013
heal.bibliographicCitation	Xydas, I., Miaoulis, G., Bonnefoi, P.-F., Plemenos, D. and Ghazanfarpour, D. (2013). Using visual analytics for web intrusion detection. "e-Journal of Science & Technology". [Online] 8(4): 1-14. Available from: http://e-jst.teiath.gr/	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 paper we describe an ongoing surveillance prototype system which offers a visual aid to the web and 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. Artificial Intelligence is combined with Visualization to detect and display unauthorized web traffic.	en
heal.publisher	Νερατζής, Ηλίας	el
heal.publisher	Σιανούδης, Ιωάννης	el
heal.journalName	e-Journal of Science & Technology	en
heal.journalName	e-Περιοδικό Επιστήμης & Τεχνολογίας	el
heal.journalType	peer-reviewed
heal.fullTextAvailability	true