The funding backs continued innovation in production-grade forecasting, anomaly detection, and artificial intelligence.

Secure your MCP metadata streams with post-quantum encryption and AI-driven anomaly detection. Learn to stop puppet attacks and tool poisoning in AI infrastructure.

The framework encompasses two principal phases: the offline model training phase and the online anomaly detection phase. During the offline model training phase, we first preprocess the raw MTS. We ...

Artificial intelligence has just turned one of astronomy’s most familiar workhorses into a discovery engine all over again.

Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods which focused on characterizing past threats. Adaptive anomaly detection ...

├── src/ # Source code modules │ ├── lstm_model.py # LSTM implementation with PyTorch │ ├── forecasting_models.py # ARIMA, Prophet, and statistical models │ ├── anomaly_detection.py # Anomaly ...

Information and communication technology (ICT) is crucial for maintaining efficient communications, enhancing processes, and enabling digital transformation. As ICT becomes increasingly significant in ...

ABSTRACT: Purpose: The purpose of this study is to develop a scalable, risk-aware artificial intelligence (AI) framework capable of detecting financial fraud in high-throughput digital transaction ...

Abstract: In recent years, Artificial Intelligence for IT Operations (AIOps) has gained popularity as a solution to various challenges in IT operations, particularly in anomaly detection. Although ...