"Synthesizing Intrusion Detection System Test Data"

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Presented at LangSec Workshop 2023 by

Intrusion Detection Systems (IDS) act as a first line of defense for network infrastructure by identifying malicious traffic and reporting it to administrators. Signature-based IDS identify this traffic by attempting to parse packets according to user-supplied rules based on well-known examples of bad traffic. However, test data can be difficult to come by (due to its sensitive nature) which makes evaluating new rules difficult. In this work we discuss the limitations of an existing SMT-based synthesis approach to automatically generating malicious network traffic. We then present a survey of how IDS rules are written in practice using an open-source corpus of over 30,000 rules and discuss a road-map towards extending the existing approach with the goal of generating security test data characterizing a broad range of threats, as well as ancillary uses assisting users in writing IDS rules and identifying IDS implementation bugs. Finally, we share early results from an evaluation of one such extension which successfully generated IDS test data for over 90% of the rules evaluated.