What is this? This is my Software Engineering final year project for University from about 2003. I used to be work in the Fraud Detection industry (mortgage and credit card fraud) and this project was to solve a problem that I had found in the telecoms industry: fraudulent phone calls. It was impossible (for me) to get phone records from telecoms companies, so I had to build a tool that would model fraudulent calls and normal call patterns, I then had to build a tool that would detect calls that were fradulent from all of the call records.
This excerpt from my final year project explores different types of telecom fraud, which I'll use as a basis for a C# neural network. Telecom fraud can be categorized into subscription fraud (false identities or payment evasion), call surfing (unauthorized network access through methods like call forwarding or cloning), ghosting (manipulating systems to avoid billing), accounting fraud (internal manipulation of billing systems), and information abuse (misuse of client or system data). I discuss the financial impact of these methods, such as bad debt from subscription fraud and costs incurred from call surfing via PABX manipulation. I also touch upon the vulnerabilities of older analogue mobile phones to cloning and the methods used in ghosting, like tone generating hardware. The project aims to address these fraud types through a neural network approach.
I've finally uploaded my final year project, even amidst a house move and lack of internet! It explores how neural networks can detect telecom fraud. I've also built a related application, but I'll share more details later. Stay tuned for more insights from the project.
I'm revisiting my final year university project on telecoms fraud detection. I built a system that generated call records and used a MATLAB neural network to analyze them for fraud. It worked surprisingly well! Now, I'm planning to rebuild the neural network in C# as a learning exercise to understand the underlying algorithms better. I'll be blogging about the project, neural networks, and the C# development process.
