Turkish Journal of Computer and Mathematics Education
Journal license

Journal

Turkish Journal of Computer and Mathematics Education


Volume
& Issue

Volume 15, Issue 1


Published
on


Pages

96-99


DOI

Article

Detection of Fraudulent or Deceptive Phone Calls Using Artificial Intelligence


Authors

J. Ratnakumari Affiliation:
Department of CSE & AI, Chalapathi Institute of Engineering and Technology, LAM, Guntur, Andhra Pradesh, India
, Shaik Nailo Asmin Thaheenath Affiliation:
Department of CSE & AI, Chalapathi Institute of Engineering and Technology, LAM, Guntur, Andhra Pradesh, India
, Tolusuri Sri Lakshmi Affiliation:
Department of CSE & AI, Chalapathi Institute of Engineering and Technology, LAM, Guntur, Andhra Pradesh, India
, Peravali Naga Dileep Kumar Affiliation:
Department of CSE & AI, Chalapathi Institute of Engineering and Technology, LAM, Guntur, Andhra Pradesh, India
and Kadiyam Veeraiah Affiliation:
Department of CSE & AI, Chalapathi Institute of Engineering and Technology, LAM, Guntur, Andhra Pradesh, India


Abstract

With an increase advancement of technology, fraud phone calls, including spam's and malicious calls have become a major concern in telecommunication industry and causes millions of global financial losses every year. Fraudulent phone calls or scams and spams via telephone or mobile phone have become a common threat to individuals and organizations. Artificial Intelligence (AI) and Machine Learning (ML) has emerged as powerful tools in detecting and analyzing fraud or malicious calls. This project presents an overview of AI-based fraud or spam detection and analysis techniques, along with its challenges and potential solutions. The novel fraud call detection approach is proposed that achieved high accuracy and precision. The Proposed approach was evaluated using a dataset of real-world fraudulent calls. And results demonstrate that the approach achieved high accuracy in detecting malicious calls and identifying potential indicators of frauds or spam's. The analysis of fraud calls also provided insights into the tactics and methods employed by fraudsters, which can be used to develop countermeasures.


Keywords

Malicious, Artificial Intelligence, Fraudulent, Machine learning


Citation

Ratnakumari, J., Thaheenath, S. N. A., Lakshmi, T. S., Kumar, P. N. D., & Veeraiah, K. (2024). Detection of fraudulent or deceptive phone calls using artificial intelligence. Turkish Journal of Computer and Mathematics Education, 15(1), 96–99.

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