International Journal For Multidisciplinary Research

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

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 6 Issue 6
November-December 2024

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

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
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 6 Isu 6Cover Page Vol 6 Isu 5Cover Page Vol 6 Isu 4

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9898-5948-55 editor@ijfmr.com