New research indicates that banks are increasingly relying on machine learning, advanced analytics, and data-driven systems to identify, assess, and mitigate risks ranging from credit defaults to ...

Researchers in Moroco analyzed cybersecurity challenges in smart grids, highlighting AI-driven detection and defense ...

An international reserch team developed two deep learning-based IDS models to enhance cybersecurity in SCADA systems. The ...

ISO/PAS 8800, focused on safety of AI applications in road vehicles, can also serve engineers in medical, industrial, rail, ...

The increasing complexity of modern chemical engineering processes presents significant challenges for timely and accurate anomaly detection. Traditional ...

Abstract: Credit card fraud detection presents a significant challenge due to the extreme class imbalance in transaction datasets. Traditional machine learning models struggle to achieve high recall ...

According to God of Prompt on Twitter, a proactive cyberdefense plan should employ AI for early threat detection, continuous network monitoring, and regular defense updates. As reported by the God of ...

Abstract: The explosive growth of the Internet of Things (IoT) has introduced vast amounts of data and unprecedented security challenges, making effective anomaly detection in IoT environments a ...

Launching a digital wallet today involves far more than enabling payments. As the digital wallet trends 2026 show high adoption of digital wallets, so do the challenges like increasingly sophisticated ...

src/ # Core system ├── monitoring/ # Resource collection ├── preprocessing/ # Data cleaning & feature engineering ├── anomaly_detection/ # ML model (Isolation Forest) ├── adaptive_engine/ # Decision ...