The Prevention Layer blocks fraud before the impression level, working for Facebook Audience Network, SDK Networks, and Performance DSP. It protects eCPI and the number of paid installs or conversions, making it suitable for the iOS 14 and SKAdNetwork era.
02
Detection Layer
The Detection Layer uses state-of-the-art AI algorithms to identify complex types of fraud in already attributed installs. It analyzes thousands of data points to detect anomalies in traffic or user behavior, including AI-enabled fraud such as click spam, click injection, device farms, smart bots, VTA spoofing, and human activity.
03
Scalarr Neural Networks
Scalarr Neural Networks are machine learning models consisting of hundreds of neurons capable of recognizing hidden fraud patterns and making associations beyond human comprehension. They can process billions of data points simultaneously and self-train, leading to increased accuracy in fraud detection.
04
Unsupervised Machine Learning
The Unsupervised Machine Learning algorithm identifies fraud patterns from large, complex unstructured data without labeling or training, enabling detection of advanced fraud types.
05
Semi-Supervised Machine Learning
The Semi-Supervised Algorithm learns from both unlabeled and labeled data, utilizing unlabeled data within a supervised learning framework. It includes a supervised fuzzy rule base generator that uses a heuristic approach to interpret outputs and explain fraud patterns.
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