DGRMiner: Anomaly Detection and Explanation in Dynamic Graphs
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F16%3A00091413" target="_blank" >RIV/00216224:14330/16:00091413 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-46349-0_27" target="_blank" >http://dx.doi.org/10.1007/978-3-319-46349-0_27</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-46349-0_27" target="_blank" >10.1007/978-3-319-46349-0_27</a>
Alternative languages
Result language
angličtina
Original language name
DGRMiner: Anomaly Detection and Explanation in Dynamic Graphs
Original language description
Ubiquitous network data has given rise to diverse graph mining and analytical methods. One of the graph mining domains is anomaly detection in dynamic graphs, which can be employed for fraud detection, network intrusion detection, suspicious behaviour identification, etc. Most existing methods search for anomalies rather on the global level of the graphs. In this work, we propose a new anomaly detection and explanation algorithm for dynamic graphs. The algorithm searches for anomaly patterns in the form of predictive rules that enable us to examine the evolution of dynamic graphs on the level of subgraphs. Specifically, these patterns are able to capture addition and deletion of vertices and edges, and relabeling of vertices and edges. In addition, the algorithm outputs normal patterns that serve as an explanation for the anomaly patterns. The algorithm has been evaluated on two real-world datasets.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Intelligent Data Analysis XV - 15th International Symposium, IDA 2016
ISBN
9783319463483
ISSN
0302-9743
e-ISSN
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Number of pages
12
Pages from-to
308-319
Publisher name
Springer
Place of publication
Neuveden
Event location
Stockholm, Sweden
Event date
Oct 13, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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