In his paper “Malware Detection Using Machine Learning” Dragos Gavrilut aimed for developing a detection system based on several modified perceptron algorithms. For different algorithms, he achieved ...

Welcome to the Attack Detection with Machine Learning repository. This project focuses on identifying malicious traffic in network systems using machine learning techniques. By leveraging various ...

Interested in understanding how AI and machine learning are being used to prevent bot-based fraud attempts, I attended a few recent webinars with Kount's 3 Key Elements Needed For Successful Bot ...

No matter the type of fraud, machine learning is a powerful tool to keep it from becoming a serious problem — regardless of how our circumstances may change.

Automated anomaly detection: Using machine learning to rapidly identify known bad behaviors is a great use case for security. After first profiling devices and understanding regular activities, ...

Azure Cognitive Services enters a new AI area. Fortunately, the first new cognitive service to explore other aspects of machine learning entered beta recently: adding anomaly detection to the ...

Java users can integrate ML into their Spring applications with Spring Boot Starter for Deep Java Library. Apply these frameworks to integrate ML capabilities into microservices for deep learning.

You have a problem: Businesses all over the world are facing a serious issue. Employees are increasingly overworked, disengaged, and bogged down by inefficient processes. A Gallup poll of more than 80 ...