International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Identifying Fraudsters and Fraudulent Strategies in Mobile Social Network

Author(s) G.Bhanuprakash Reddy, A.Shruthi, V.Srikanth, J. Jyotsna
Country India
Abstract Modern communication technologies have developed quickly, especially communications through (mobile) phones, which has greatly aided in the sharing of information and social connections between people. Nonetheless, the rise of telemarketing scams has the potential to seriously deplete communal and private wealth, slowing down or harming the economy. With an emphasis on exposing the "precise fraud" phenomena and the techniques employed by fraudsters to precisely choose targets, we propose to identify telemarketing scams in this study. We utilise a one-month comprehensive dataset of telecommunication information from Shanghai, which includes 698 million call logs and 54 million customers, to explore this issue. During our research, we have discovered that user information may have been substantially compromised, and that fraudsters prefer to target users who are younger and more active on mobile networks. To further separate fraudsters from non-fraudsters, we provide a unique semi-supervised learning approach. Our technique beats various cutting-edge algorithms in terms of accuracy of identifying fraudsters, according to experimental findings on real-world data. We think that our research may help governments and mobile service providers make better policy decisions.
Keywords Precise fraud, Semi-Supervised Machine Learning.
Field Engineering
Published In Volume 5, Issue 2, March-April 2023
Published On 2023-04-24
Cite This Identifying Fraudsters and Fraudulent Strategies in Mobile Social Network - G.Bhanuprakash Reddy, A.Shruthi, V.Srikanth, J. Jyotsna - IJFMR Volume 5, Issue 2, March-April 2023. DOI 10.36948/ijfmr.2023.v05i02.2622
DOI https://doi.org/10.36948/ijfmr.2023.v05i02.2622
Short DOI https://doi.org/gr6h69
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