A COMPREHENSIVE REVIEW OF FRAUDULENT ACTIVITY TRACKING AND DETECTION TECHNIQUES

【Author】 Prabha, N.; Manimekalai, S.

【Source】ADVANCES AND APPLICATIONS IN MATHEMATICAL SCIENCES

【影响因子】0.000

【Abstract】This review paper represents the various automated fraud detection techniques to categorize and comparison of important published articles. There are different methods and techniques are used to detect the multiple fraud activities in network security and online transactions. Nowadays, online fraud activities main issue in the network society. Because every second's thousands of activities online fraudulent activities held in the society. The fraudulent detection techniques classified as proactive and reactive methods. Based on the analysis of existing research the fraud detection techniques are implemented in the concepts of data mining, graph flow control, artificial intelligence, machine learning, Blockchain Technology and IoT etc. The novelty of this paper is presenting the type of relevant data-mining, graph flow techniques and electronic fraud-based fraud detection techniques and it's a comparison of standard methods with multiple parameters presented in this article. The parameters compared with classification, types of problems and predictions etc. The finally various issues, challenges and future feasible possible methodologies are presented.

【Keywords】Fraudulent Detection Techniques; data mining; Artificial intelligence; machine learning; Graph based prediction

【发表时间】2021 OCT

【收录时间】2022-02-05

【文献类型】综述

【主题类别】

综述--