Scams and Frauds in the Digital Age: ML-Based Detection and Prevention Strategies
Sai Venkata Jaswant Kolupuri, Ananya Paul, Rajat Subhra Bhowmick, Isha Ganguli
Abstract
Over the past two decades, the commercial landscape has undergone a transformation, shifting from traditional marketing methods to digital and internet-based platforms.This shift, while boosting economic potential, has also made the digital world a prime target for cybercriminals.Online scams and fraud have become prevalent, affecting individuals and businesses globally.Financial losses from cyber fraud in India have surged significantly, rising from Rs 69.7 crore in FY 2023 to Rs 177.05 crore in FY 2024.This paper presents a detailed analysis of various forms of online scams and frauds, explaining their core methodologies and the severe impacts these schemes have on consumers.From phishing and identity theft to sophisticated financial fraud, the study dives deep into how these fraudulent activities evolve and adapt to target individuals and businesses alike.The paper also offers a thorough taxonomy of each type of scam to provide a structured understanding of the different fraud strategies.The paper highlights a range of Machine Learning (ML) and Deep Learning (DL) methods that are essential in identifying fraudulent patterns in real-time.In addition to these detection methods, the paper also outlines several ML/DL-based prevention strategies aimed at proactively stopping scams before they cause harm.Ultimately, by promoting advanced detection and prevention methods, this document aims to contribute to the development of a safer digital ecosystem.