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This allows us to extract several families of features. Some of them require careful feature engineering, while others are more general and follow well-known NLP techniques. Next, we survey prior art from the literature and discuss several natural approaches to this problem.
Finally, we suggest obfuscator-agnostic methods to build state-of-the-art machine learning classifier for this problem.
Yuriy Arbitman Data Scientist, Imperva
As a data scientist in Imperva, I develop machine learning solutions for various cyber security projects. I'm fascinated by the wonders that data science and machine learning bring to the world. The wealth of open-source frameworks enable us to build systems today at scale and ease unthinkable just several years ago. In the last 20+ years I've been working in the hi-tech industry in Israel. I am lucky to have worked for several great companies in engineering, management and research positions. I hold an M.Sc. in Computer Science from the Weizmann Institute in Israel.