Gibberish Detection analyzes the text of an email address to classify the likelihood of randomness or automation using ...

Trends such as the increased accessibility of “deepfake” technologies will likely accelerate this year, allowing bad actors ...

Together, they create an infrastructure layer designed for a world where attacks are automated, data is abundant and digital ...

Abstract: Machine Learning (ML) algorithms are robust in addressing complex challenges, such as detecting financial fraud in real-world scenarios. This research highlights the significance of ML ...

Proactive monitoring tools, such as a third-party hotline platform and data analytics, coupled with employee engagement and a ...

Explainable AI plays a central role in validating model behavior. Using established explainability techniques, the study examines which financial variables drive fraud predictions. The results show a ...

Amirali Aghazadeh receives funding from Georgia Tech. When NASA scientists opened the sample return canister from the OSIRIS-REx asteroid sample mission in late 2023, they found something astonishing.

What’s driving the rise in digital fraud? The global payments landscape appears more dynamic and complex than ever before. As e-commerce spending accelerates toward an estimated $8.1 trillion by 2028, ...

You’re managing a federal agency contact center when someone calls in with a bomb threat targeting a government building. The employee immediately begins working to obtain as much information from the ...

Advanced fraud detection system using machine learning to identify fraudulent transactions and activities. This project implements multiple machine learning algorithms including Random Forest, XGBoost ...