Title
Anomaly detection for internet surveillance
Author
Bouma, H.
Raaijmakers, S.A.
Halma, A.H.R.
Wedemeijer, H.
Contributor
Ternovskiy, I.V. (editor)
Chin, P. (editor)
Publication year
2012
Abstract
Many threats in the real world can be related to activity of persons on the internet. Internet surveillance aims to predict and prevent attacks and to assist in finding suspects based on information from the web. However, the amount of data on the internet rapidly increases and it is time consuming to monitor many websites. In this paper, we present a novel method to automatically monitor trends and find anomalies on the internet. The system was tested on Twitter data. The results showed that it can successfully recognize abnormal changes in activity or emotion. Many threats in the real world can be related to activity of persons on the internet. Internet surveillance aims to predict and prevent attacks and to assist in finding suspects based on information from the web. However, the amount of data on the internet rapidly increases and it is time consuming to monitor many websites. In this paper, we present a novel method to automatically monitor trends and find anomalies on the internet. The system was tested on Twitter data. The results showed that it can successfully recognize abnormal changes in activity or emotion.
Subject
Anomaly detection
Internet surveillance
Data mining
Forensics
Cybercrime
Pattern recognition
ETP SON-M
Safety and Security
Defence, Safety and Security
Physics & Electronics ; Communication & Information GI Innovation in Behaviour / Gedrag en Innovatie
II - Intelligent Imaging ; MNS - Media & Network Services
TS - Technical Sciences
To reference this document use:
http://resolver.tudelft.nl/uuid:a48c14ce-d1b4-41d8-83c5-fc336b08cd35
DOI
https://doi.org/10.1117/12.918573
TNO identifier
460364
Publisher
SPIE, Bellingham, WA
Source
Cyber Sensing 2012, 24 April 2012, Baltimore, MD, USA
Series
Proceedings of SPIE
Document type
conference paper