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CybersecuritySecurity NewswireAccess ManagementIdentity Management

Using Machine Learning to Fight Fraud, Redirect Security Strategies and Protect Users

By Kevin Lee

By now, everyone has heard of fake news, aka, misinformation, or propaganda. While false or misleading news precedes the internet, fake news has now become a singular part of a much larger problem in the digital world called content abuse. This includes any form of user generated content that is malicious in nature--trolling, bullying, harassment, fake reviews and social engineering scams that play on our emotions to trick us into handing over money, data, or in the case of the recent 2016 presidential election scandal involving Facebook and consulting firm Cambridge Analytica, our votes.

Digital identities are rapidly growing, and with more and more users online - we have a reported 3.8 billion users online as of 2017 - criminals, armed with machine learning technologies, are gaining access to an increasing amount of information they can use to identify and exploit our vulnerabilities. On the flip side of this, machine learning has proven a powerful force in fighting back against fraudsters, malicious content, abuse and more. Without it, businesses are running on antiquated methods for identifying fraud, fraudsters stay a step ahead, and the cost to businesses can be very high.

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