681 citations · 2.9k across the 62 of their papers we have counts for
10 papers · 1 filter
Characterizing Service Provider Response to the COVID-19 Pandemic in the United States
Shinan Liu, Paul Schmitt, Francesco Bronzino +1
The COVID-19 pandemic has resulted in dramatic changes to the daily habits of billions of people. Users increasingly have to rely on home broadband Internet access for work, educat…
Traffic Refinery: Cost-Aware Data Representation for Machine Learning on Network Traffic
Francesco Bronzino, Paul Schmitt, Sara Ayoubi +3
Network management often relies on machine learning to make predictions about performance and security from network traffic. Often, the representation of the traffic is as importan…
New Directions in Automated Traffic Analysis
Jordan Holland, Paul Schmitt, Nick Feamster +1
Despite the use of machine learning for many network traffic analysis tasks in security, from application identification to intrusion detection, the aspects of the machine learning…
Can Encrypted DNS Be Fast?
Austin Hounsel, Paul Schmitt, Kevin Borgolte +1
In this paper, we study the performance of encrypted DNS protocols and conventional DNS from thousands of home networks in the United States, over one month in 2020. We perform the…
Classifying Network Vendors at Internet Scale
Jordan Holland, Ross Teixeira, Paul Schmitt +4
In this paper, we develop a method to create a large, labeled dataset of visible network device vendors across the Internet by mapping network-visible IP addresses to device vendor…
Feature Extraction for Novelty Detection in Network Traffic
Kun Yang, Samory Kpotufe, Nick Feamster
Data representation plays a critical role in the performance of novelty detection (or ``anomaly detection'') methods in machine learning. The data representation of network traffic…