explain the result Adversarial ML Moreover, deep learnings are good at finding or generating similar things The result may not be intuitive. Signal fatigue. Poisoning attacks, evasion attacks. Challenges IUUQTXFCTUBOGPSEFEVDMBTTDTEMFDUVSFT4FTTJPOQEG
for each users - Time-series prediction on overall traffic How are we doing? Access log Logstash Elastic search User-level detection Overall detection Alarm system
Forest: An application to plasma etching.” Isolation Forest - Partitioning the space until we can isolate the point - Less number of partition means more anomaly Anomaly scoring
Forest: An application to plasma etching.” Isolation Forest - Partitioning the space until we can isolate the point - Less number of partition means more anomaly Anomaly scoring
ML - Still it’s better than manual detection - There’s no silver bullet solution - Open subject - More models are robust, but hard to harmonize them Summary
Sander. "Density-based clustering based on hierarchical density estimates." Pacific-Asia conference on knowledge discovery and data mining. Springer, Berlin, Heidelberg, 2013. - Hariri, Sahand, Matias Carrasco Kind, and Robert J. Brunner. "Extended Isolation Forest." arXiv preprint arXiv: 1811.02141 (2018). - Taylor, Sean J., and Benjamin Letham. "Forecasting at scale." The American Statistician 72.1 (2018): 37-45. References