• Corpus ID: 212585784

A Survey on Hidden Markov Model for Credit Card Fraud Detection

@inproceedings{Singh2012ASO,
  title={A Survey on Hidden Markov Model for Credit Card Fraud Detection},
  author={Anshul Singh and Devesh Narayan},
  year={2012}
}
Credit card frauds are increasing day by day regardless of the various techniques developed for its detection. Fraudsters are so expert that they engender new ways for committing fraudulent transactions each day which demands constant innovation for its detection techniques as well. Many techniques based on Artificial Intelligence, Data mining, Fuzzy logic, Machine learning, Sequence Alignment, decision tree, neural network, logistic regression, naïve Bayesian, Bayesian network, metalearning… 

Figures and Tables from this paper

Credit Card Fraud Detection Using Hidden Markov Model (HMM)

This paper presents technique used in credit card fraud detection mechanism using hidden markov model, which has evolved in detecting various credit card fraudulent transactions.

A Revived Survey of Various Credit Card Fraud Detection Techniques

This paper represents a survey of various techniques used in credit card fraud detection mechanisms based on Neural Network, Artificial Intelligence, Bayesian Network, Data mining, Artificial Immune System, K- nearest neighbor algorithm, Decision Tree, Fuzzy Logic Based System, Support Vector Machine, Machine learning, Genetic Programming etc., that has developed in detecting various credit card fraudulent transactions.

Credit Card Fraud Detection System Using Hidden Markov Model and K-Clustering

A new approach for credit card fraud detection using Hidden Markov Model (HMM) is proposed and it is shown how fraud can be detected as well as survey of various techniques has been done.

Fraudulent credit card transaction detection using soft computing techniques

This paper initially analyses the data through exploratory data analysis and then proposes various classification models that are implemented using intelligent soft computing techniques to predictively classify fraudulent credit card transactions that can be used for credit card fraudulent transaction detection with better accuracy.

A Secured Approach to Credit Card Fraud Detection Using Hidden Markov Model

HOTP is used as secured approach with HMM to reduce the fraud and to increase the security and it is shown that hidden markov model is used to detect credit card fraud with reduced false positive transaction.

Credit Card Fraud Detection System using HMM and Image Click Point Authentication

The proposed system gives the solution for identification of most likely image regions to users and the user has to click on region of image for creation of graphical authentication in the Image Click Point Authentication System (ICPA).

Analysis on Credit Card Fraud Detection Techniques: Based on Certain Design Criteria

A survey of various techniques used in credit card fraud detection and evaluates each methodology based on certain design criteria is presented.

Investigation of Credit Card Fraud Recognition Techniques based on KNN and HMM

KNN algorithm and HIDDEN MARKOV MODEL is implemented to optimize the best solution for the problem and this approach is proved to minimize the false alarm rates and increase the fraud detection rate.

A Predictive Approach for Fraud Detection Using Hidden Markov Model

A model with sequence of operations in online transaction by using hidden markov model (HMM) and decides whether the user act as a normal user or fraud user and predicts the fraudulent during the transaction time and prevents the money transfer.

A Survey of Credit Card Fraud Detection Techniques: Data and Technique Oriented Perspective

Open issues for credit card fraud detection are explained as guidelines for new researchers and a classification of techniques into two main fraud detection approaches, namely, misuses (supervised) and anomaly detection (unsupervised), is presented.

References

SHOWING 1-10 OF 33 REFERENCES

Credit Card Fraud Detection Using Hidden Markov Model

This paper model the sequence of operations in credit card transaction processing using a hidden Markov model (HMM) and shows how it can be used for the detection of frauds and compares it with other techniques available in the literature.

Distributed data mining in credit card fraud detection

The proposed methods of combining multiple learned fraud detectors under a "cost model" are general and demonstrably useful; the empirical results demonstrate that they can significantly reduce loss due to fraud through distributed data mining of fraud models.

Mining information from credit card time series for timelier fraud detection

In this research, a profiling method has been proposed for credit card fraud detection that focuses on fraud cases which cannot be detected at the transaction level, using patterns inherent in the time series of aggregated daily amounts spent on an individual credit card account.

Neural data mining for credit card fraud detection

This paper shows how advanced data mining techniques and a neural network algorithm can be combined successfully to obtain a high fraud coverage combined with a low false alarm rate.

Detection of fraud use of credit card by extended VFDT

This paper proposes and implements new statistical criteria to be used in a node-construction algorithm that implements Very Fast Decision Tree learner (VFDT), and evaluates whether this method can be supported in imbalanced distribution data streams.

Research on Credit Card Fraud Detection Model Based on Class Weighted Support Vector Machine

An improved SVM--Imbalance Class Weighted SVM (ICW-SVM) was adopted and it is demonstrated that this model is more suitable for solving credit card fraud detection problem with higher precision and effective than others.

Statistical fraud detection: A review

This work describes the tools available for statistical fraud detection and the areas in which fraud detection technologies are most used, and statistics and machine learning provide effective technologies for fraud detection.

Agent-Based Distributed Learning Applied to Fraud Detection

An AI-based approach that supports the cooperation among different institutions and consists of pattern-directed inference systems that use models of anomalous or errant transaction behaviors to forewarn of fraudulent practices is described.

Improving a credit card fraud detection system using genetic algorithm

This study undertook the credit card fraud detection problem of a bank and tried to improve the performance of an existing solution by making an application of genetic algorithms which is a novel one in the related literature both in terms of the application domain and the cross-over operator used.