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Uncovering Unknown Threats With Human-Readable Machine Learning

In this blog post, we will discuss how we developed a human-readable machine learning system that is able to determine whether a downloaded file is benign or malicious in nature.
The development of this actionable intelligent system stemmed from the question: How can we make our knowledge about global software download events actionable? More specifically, how can we use such information to do a better job at detecting the threats posed by the large amounts of new malicious software circulating on a daily basis?
In this last installment of this blog series, we will answer such questions and give a summary of what we did with the information we’ve obtained. Our research paper titled Exploring the Long Tail of (Malicious) Software Downloads provides a more comprehensive look into how we’ve gathered and analyzed our software downloads data.
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