Summary

This chapter focused on two important problems in security and privacy. We began by discussing authorship attribution, a task of identifying who wrote a particular piece of text. We designed a series of linguistic and text-based features and trained ML models for authorship attribution. Then, we turned to authorship obfuscation, a task that aims to evade the attribution models by making changes to the text such that author-identifying characteristics and style markers are removed. We looked at a series of obfuscation methods for this. For both tasks, we looked at the improvements that could be made to the performance.

Both authorship attribution and obfuscation have important applications in cybersecurity. Attribution can be used to detect Sybil accounts, trace cybercriminals, and protect intellectual property rights. Similarly, obfuscation can help preserve the anonymity of individuals and provide privacy guarantees. This chapter enables ML practitioners in cybersecurity...