Ariana Mirian
Ariana Mirian currently works as a senior security researcher at Censys, where she uses Internet Measurement to answer interesting security questions. Prior to Censys, she received her PhD from UCSD, where her thesis focused on answering the question: how can we use large scale measurement and analysis to better prioritize security processes? When not geeking out about Internet Measurement and security, Ariana is also an avid aerialist and birder.
Session
Last year, we learned a key truth: not everything on the Internet is forever, and there is far more variability in host lifespan across different ports, protocols, and networks than we initially thought. Today, we’re going to focus on how we moved beyond the descriptive analyses to ask the next natural question: Given all this variability, how can we actually predict the lifespan of a host?
In this talk, I invite participants to dive down the ML rabbit hole with me. I’ll walk through how our research questions evolved, where our early methods/initial attempts failed, and what we learned from those failures to finally arrive at a practical solution. While ML has improved many aspects of our lives, applying it to solve problems in niche, high-noise areas like security and the Internet-wide measurement space is not always straightforward. With the right tweaks and persistence, we found a path forward, and I hope that audience members walk away with a better understanding of some of these ML pitfalls, as well as a way to think about how to apply ML to their own similarly gnarly problems, using our case study as an example.