A survey of intrusion detection techniques
Computers and Security
Discovery of fraud rules for telecommunications—challenges and solutions
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Communications of the ACM
Data Mining and Knowledge Discovery
Signature-Based Methods for Data Streams
Data Mining and Knowledge Discovery
Detection of Mobile Phone Fraud Using Supervised Neural Networks: A First Prototype
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
Detecting fraud in the real world
Handbook of massive data sets
Systematic data selection to mine concept-drifting data streams
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Belief state approaches to signaling alarms in surveillance systems
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Metadata for Anomaly-Based Security Protocol Attack Deduction
IEEE Transactions on Knowledge and Data Engineering
A Survey of Outlier Detection Methodologies
Artificial Intelligence Review
Outlier Detection with Explanation Facility
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Modelling call detail records from a mobile telecommunications network
ASM '07 The 16th IASTED International Conference on Applied Simulation and Modelling
Outlier Detection with a Hybrid Artificial Intelligence Method
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
Applying user signatures on fraud detection in telecommunications networks
ICDM'11 Proceedings of the 11th international conference on Advances in data mining: applications and theoretical aspects
Parameter-free anomaly detection for categorical data
MLDM'11 Proceedings of the 7th international conference on Machine learning and data mining in pattern recognition
Expert Systems with Applications: An International Journal
Detecting abnormal patterns in call graphs based on the aggregation of relevant vertex measures
ICDM'12 Proceedings of the 12th Industrial conference on Advances in Data Mining: applications and theoretical aspects
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All over the world we have been assisting to a significant increase of the telecommunication systems usage. People are faced day after day with strong marketing campaigns seeking their attention to new telecommunication products and services. Telecommunication companies struggle in a high competitive business arena. It seems that their efforts were well done, because customers are strongly adopting the new trends and use (and abuse) systematically communication services in their quotidian. Although fraud situations are rare, they are increasing and they correspond to a large amount of money that telecommunication companies lose every year. In this work, we studied the problem of fraud detection in telecommunication systems, especially the cases of superimposed fraud, providing an anomaly detection technique, supported by a signature schema. Our main goal is to detect deviate behaviors in useful time, giving better basis to fraud analysts to be more accurate in their decisions in the establishment of potential fraud situations.