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

The text discusses how to protect APIs against sequential abuse using statistical machine learning techniques. It introduces the concept of API sessions and how they can be used to identify malicious activities by analyzing the order in which requests are made. The blog post then explains how Markov chains, specifically variable order Markov chains (VOMCs), can be applied to summarize sequential behavior from past session data and determine important sequences. Finally, it describes an efficient algorithm that updates the model continuously as data arrive, allowing for real-time analysis of API requests and protection against malicious activities.

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