C4.5: programs for machine learning
C4.5: programs for machine learning
State Transition Analysis: A Rule-Based Intrusion Detection Approach
IEEE Transactions on Software Engineering
Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Intrusion detection with neural networks
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Efficient mining of emerging patterns: discovering trends and differences
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
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
Making use of the most expressive jumping emerging patterns for classification
Knowledge and Information Systems
Machine Learning
Brief Application Description; Visual Data Mining: Recognizing Telephone Calling Fraud
Data Mining and Knowledge Discovery
Detecting Group Differences: Mining Contrast Sets
Data Mining and Knowledge Discovery
Computer
Web Services and Business Transactions
World Wide Web
CAEP: Classification by Aggregating Emerging Patterns
DS '99 Proceedings of the Second International Conference on Discovery Science
Neural Data Mining for Credit Card Fraud Detection
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
An introduction to variable and feature selection
The Journal of Machine Learning Research
Mining with rarity: a unifying framework
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Minority report in fraud detection: classification of skewed data
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Rapid detection of significant spatial clusters
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
On Designing a Flexible E-Payment System with Fraud Detection Capability
CEC '04 Proceedings of the IEEE International Conference on E-Commerce Technology
On the complexity of finding emerging patterns
Theoretical Computer Science - Pattern discovery in the post genome
Using artificial anomalies to detect unknown and known network intrusions
Knowledge and Information Systems
Training Cost-Sensitive Neural Networks with Methods Addressing the Class Imbalance Problem
IEEE Transactions on Knowledge and Data Engineering
Offline Internet Banking Fraud Detection
ARES '06 Proceedings of the First International Conference on Availability, Reliability and Security
Authentication in an Internet Banking Environment; Towards Developing a Strategy for Fraud Detection
ICISP '06 Proceedings of the International Conference on Internet Surveillance and Protection
Envisioning intelligent information technologies through the prism of web intelligence
Communications of the ACM - Emergency response information systems: emerging trends and technologies
World Wide Web
A study in using neural networks for anomaly and misuse detection
SSYM'99 Proceedings of the 8th conference on USENIX Security Symposium - Volume 8
The Use of Attack and Protection Trees to Analyze Security for an Online Banking System
HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
Data mining approaches for intrusion detection
SSYM'98 Proceedings of the 7th conference on USENIX Security Symposium - Volume 7
Credit Card Fraud Detection Using Hidden Markov Model
IEEE Transactions on Dependable and Secure Computing
Real-time credit card fraud detection using computational intelligence
Expert Systems with Applications: An International Journal
Security and usability: the gap in real-world online banking
NSPW '07 Proceedings of the 2007 Workshop on New Security Paradigms
Metasynthesis: M-space, M-interaction, and M-computing for open complex giant systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Credit Fraud Detection in the Banking Sector in UK: A Focus on E-Business
ICDS '10 Proceedings of the 2010 Fourth International Conference on Digital Society
Neural fraud detection in credit card operations
IEEE Transactions on Neural Networks
Combined Mining: Discovering Informative Knowledge in Complex Data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Research challenges and perspectives on Wisdom Web of Things (W2T)
The Journal of Supercomputing
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Sophisticated online banking fraud reflects the integrative abuse of resources in social, cyber and physical worlds. Its detection is a typical use case of the broad-based Wisdom Web of Things (W2T) methodology. However, there is very limited information available to distinguish dynamic fraud from genuine customer behavior in such an extremely sparse and imbalanced data environment, which makes the instant and effective detection become more and more important and challenging. In this paper, we propose an effective online banking fraud detection framework that synthesizes relevant resources and incorporates several advanced data mining techniques. By building a contrast vector for each transaction based on its customer's historical behavior sequence, we profile the differentiating rate of each current transaction against the customer's behavior preference. A novel algorithm, ContrastMiner, is introduced to efficiently mine contrast patterns and distinguish fraudulent from genuine behavior, followed by an effective pattern selection and risk scoring that combines predictions from different models. Results from experiments on large-scale real online banking data demonstrate that our system can achieve substantially higher accuracy and lower alert volume than the latest benchmarking fraud detection system incorporating domain knowledge and traditional fraud detection methods.