Protecting APIs from abuse using sequence learning and variable order Markov chains

What this post added

This post details the application of sequence learning, specifically using variable order Markov chains (VOMCs), to enhance API security by detecting and mitigating sequential abuse. It explains how API sessions are modeled, the limitations of standard Markov chains, and how VOMCs are used to identify important API request sequences by considering credible intervals and variable context lengths. This contributes to the Sequence Analytics product by providing a more robust method for identifying malicious API request patterns that are not detectable by volumetric methods alone.