Title

Ads-Guard: Detecting Scammers in Online Classified Ads

Abstract

Classified ad platforms have become a popular way for people to sell and purchase goods and services online. Unfortunately, while convenient, sites like Craigslist carry the risk of fraud because buyers do not meet sellers face to face. Many unsuspecting buyers fall victim to online scams and lose both time and money as a result. While there is literature available advising customers on how to avoid such scams, there is currently a lack of tools to automatically detect red flags of potential scams. One method that scammers use to trick buyers online is providing a contact phone number that belongs to a Voice over Internet Protocol (VoIP) service to hide their identities. Moreover, since scammers usually do not actually have the advertised product available to sell, they tend to use images copied from elsewhere on the Internet in their ads. Scammers also typically use certain common scam keywords to trick users. In this paper, we present a tool with intelligent components that automatically detects these indicators to determine the likelihood that a given classified ad is a scam. This tool aims to protect online shoppers by helping them make well-informed decisions about the legitimacy of classified ads.

Publication Title

2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020

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