Anomaly detection for internet surveillance
| Autor: | Bouma, H., Raaijmakers, S.A., Halma, A.H.R., Wedemeijer, H. |
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| Jazyk: | angličtina |
| Rok vydání: | 2012 |
| Předmět: |
TS - Technical Sciences
Informatics Cybercrime education ETP SON-M Anomaly detection Defence Safety and Security II - Intelligent Imaging MNS - Media & Network Services Safety and Security Pattern recognition Physics & Electronics Communication & Information GI Innovation in Behaviour / Gedrag en Innovatie Internet surveillance Data mining Forensics |
| Zdroj: | Ternovskiy, I.V.Chin, P., Cyber Sensing 2012, 24 April 2012, Baltimore, MD, USA |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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