AuthSpotter: Visualizing Suspicious Logon Behavior

AuthSpotter is a data visualization project created by four students in the U.C. Berkeley Masters in Data Science (MIDS) program for the W209 Data Visualization and Communication course. The goal of this project is to use data visualization techniques in a cybersecurity context: to understand normal patterns of user logon behavior and identify unusual or suspicious logon behavior. In a real-world scenario, suspicious behavior could be analyzed further by looking at more detailed logs and/or interviewing the user in question. The intended audience is cybersecurity professionals and researchers.