This week my guest is Evan Wright, principal data scientist at cybersecurity startup Anomali. In my interview with Evan, he and I discussed about a number of topics surrounding the use of machine learning in cybersecurity.
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If Evan’s name sounds familiar, it’s because Evan was the winner of the O’Reilly Strata+Hadoop World ticket giveaway earlier this month. We met up at the conference last week and took advantage of the opportunity to record this show.
Our conversation covers, among other topics, the three big problems in cybersecurity that ML can help out with, the challenges of acquiring ground truth in cybersecurity and some ways to accomplish it, and the use of decision trees, generative adversarial networks, and other algorithms in the field.
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About Evan Wright
Mentioned in the Interview
- Anomali Web Site
- Anomali’s Modern Honey Network Project
- Domain Generation Algorithms on Wikipedia
- The Texas A&M Paper on DGAs
- Open Source Data Mining Tools: Weka, Orange, RapidMiner
- Decision Tree Induction Algorithms: ID3, C45
- Gini Impurity and Information Gain in Decision Tree Learning
- Leo Brieman
- Ensemble Learning: Bagging, Boosting & Stacking
- Evan’s paper Weakly Supervised Extraction of Computer Security Events from Twitter with Tom Mitchell and Alan Ritter