DocumentCode :
3281066
Title :
A Method for Identifying Malicious Activity in Collaborative Systems with Maps
Author :
Furtado, Vasco ; Assuncao, T. ; de Oliveira, Mauricio ; Belchior, Mairon ; D´Orleans, Jonathan
Author_Institution :
Univ. de Fortaleza, Fortaleza, Brazil
fYear :
2009
fDate :
20-22 July 2009
Firstpage :
334
Lastpage :
337
Abstract :
In this paper we describe the method we have created for the purpose of identifying misbehavior of users who intends to generate false trends in digital maps. Basically, the idea is to identify patterns of communities of users who strongly contribute with reports that lead a particular geographic area to be considered a hot spot. The association between hot spots, computed from Kernel Density Estimation techniques, and the methods for identifying communities in social networks is the main innovation of the method proposed. A multi-agent system was built in order to simulate several scenarios of malicious activities. This method has shown to be effective for alerting the possibility of malicious activity in a real system.
Keywords :
groupware; multi-agent systems; security of data; social networking (online); collaborative systems; digital maps; geographic area; kernel density estimation techniques; malicious activity identification; multiagent system; social networks; user community; user misbehavior; Collaboration; Computational modeling; Computer networks; Kernel; Monitoring; Multiagent systems; Smoothing methods; Social network services; Technological innovation; Visualization; colaborative systems; data mining; social networks; wikimapps;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Social Network Analysis and Mining, 2009. ASONAM '09. International Conference on Advances in
Conference_Location :
Athens
Print_ISBN :
978-0-7695-3689-7
Type :
conf
DOI :
10.1109/ASONAM.2009.35
Filename :
5231843
Link To Document :
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