AEGIS Lab

Optimizing AI Anomaly Detection with the Aegis CyberEngineer™ Toolbox

Feature Engineering

Overview

While the features computed and organized by the Aegis CyberXtractor™ are valuable, they are not yet optimal inputs for training accurate AI anomaly detection models. They suffer from certain limitations that need to be addressed. Firstly, they result in large-scale sparse matrices due to the presence of numerous computed features with missing or zero indicators when not applicable.  These matrices require special mathematical dimension reduction techniques. Additionally, these features may not exhibit sufficient cross-correlation, and it is crucial to compute more optimal features from them that are better suited for AI modeling. 
Aegis CyberEngineer™ toolbox greatly facilitates and accelerates AI model building by providing a no-coding approach to mathematical feature engineering. With its intuitive web dashboard, users can effortlessly perform complex mathematical operations through a simple drag-and-drop interface. This platform eliminates the need for scripting or extensive mathematical background, making it accessible to data scientists and users of all skill levels. They can focus on the core aspects of their work without being hindered by technical complexities, and save time and effort in the model development lifecycle.

Aegis CyberEngineer™

The Aegis CyberEngineer™ is a high-performance, no-coding data processing microservice designed to empower data science engineers. With its intuitive web dashboard, users can effortlessly drag and drop a sequence of mathematical processors from a pre-established library onto any set of base features. This powerful tool offers a range of functionalities:

Perform mathematical data processing routines such as data cleansing, gap filling, normalization, quantization, augmentation, etc.

Gain valuable insights into the collective behavior features by performing linear and nonlinear correlation analysis.

Generate additional computed behavior modeling features through linear and nonlinear functions applied to a number of base features.

Utilize numerous dimension reduction algorithms to streamline and optimize data.

Enhance features with contextual information such as time of day, day of the week within legal and work calendar contexts, geolocation, and more.

Cyber Security Data Lake Diagram

Dive into the Future of AI Anomaly Detection!

Unleash the full potential of your data with the Aegis CyberEngineer™ Toolbox. Streamline your processes and elevate your models – Get started today!