Date of Award

5-2024

Document Type

Project

Degree Name

Master of Science in Cybersecurity and Analytics

Department

Information and Decision Sciences

First Reader/Committee Chair

Jesus Canelon

Abstract

Online child predators pose a danger to children who use the Internet. Children fall victim to online predators at an alarming rate, based on the data from the National Center of Missing and Exploited Children. When making online profiles and joining websites, you only need a name, an email and a password without identity verification. Studies have shown that online predators use a variety of methods and tools to manipulate and exploit children, such as blackmail, coercion, flattery, and deception. These issues have created an opportunity for skilled online predators to have fewer obstacles when it comes to contacting and grooming children without parents or law enforcement knowledge. Based on early research, one could assume that companies could do more to protect children online and that stricter online communication monitoring is needed. The research for this project covers the behaviors of predators, types of internet crimes against children and artificial intelligence’s ability to detect online predators with the end goal of protecting children online. The results from the research found that artificial intelligence can detect online predators in chats and image sharing. However, more research can be done on image detection. This paper will benefit parents looking to protect their children online, law enforcement agencies and companies that have active children on their websites or applications.

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