Security vendors and their customers have spent considerable time debating where to draw the line between “legitimate” AI agents and “malicious” bots. A 31-day campaign against a major consumer ...

This study investigates whether anomaly-aware modeling can improve stock price forecasting by incorporating signals that highlight unusual market behavior. Financial time series often contain sudden ...

Evaluate the effectiveness of Microsoft’s Python Risk Identification Toolkit (PyRIT) for agentic AI red teaming. Address evolving autonomous AI system threats.

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

Detecting anomalous events in satellite telemetry is a critical task in space operations. It is time-consuming, error-prone and human dependent, thus automated data-driven algorithms have been ...

Abstract: The more the advanced image making tools become accessible, the more image forgery is proliferated in hardware and software across all these domains – forensics, journalism, authentication, ...

This guide shows how to extract time series data from Google Earth Engine (GEE) and analyze it with Python. I cover time series plotting, seasonal decomposition, anomaly detection, outlier ...

The stock market is a dynamic environment where prices and trading volumes fluctuate daily. Understanding these movements is crucial for making informed investment decisions. In this tutorial, we ...

pyCLAD is a unified framework for continual anomaly detection. Its main goal is to foster successful scientific development in continual anomaly detection by providing robust implementations of ...

Pandas is a robust data manipulation library that offers high-performance, user-friendly data structures and analytical tools in Python. Pandas enables users to import, clean, transform, and analyze ...