A new family of Android click-fraud trojans leverages TensorFlow machine learning models to automatically detect and interact ...

AI tools are exposing hidden truths in art history, analyzing brushstrokes to reveal who really painted the world’s ...

One of the most difficult challenges in payment card fraud detection is extreme class imbalance. Fraudulent transactions ...

The ability of computers to learn on their own by using data is known as machine learning. It is closely related to ...

Money laundering is on the rise, analysts say, as criminals exploit new technologies like artificial intelligence, crypto, ...

AtData, a leading innovator in email address intelligence and digital trust solutions, is introducing Gibberish Detection, a new machine learning-driven model in its fraud prevention suite that ...

Gibberish Detection analyzes the text of an email address to classify the likelihood of randomness or automation using indicators such as pattern anomalies and likely bot behavior. The resulting ...

ABSTRACT: Context and Justification: As financial services undergo accelerated digitalization, the expansion of electronic transactions within digital wallets increases vulnerabilities to fraud, ...

ABSTRACT: Improved accuracy in predicting corporate financial fraud significantly enhances regulatory efficiency and market stability. However, detecting increasingly sophisticated fraud patterns ...

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.

Fraud detection is no longer enough to protect today’s financial ecosystem. As digital transactions increase in volume and complexity, banks require intelligent systems that can assess risk with ...