Chen Chang Lew, Christof Ferreira Torres, et al.
EuroS&P 2024
The article describes a practical method for detecting outlier database connections in real-time. Outlier connections are detected with a specified level of confidence. The method is based on generalized security rules and a simple but effective real-time machine learning mechanism. The described method is non-intrusive to the database and does not depend on the type of database. The method is used to proactively control access even before database connection is established, minimize false positives, and maintain the required response speed to detected database connection outliers. The capabilities of the system are demonstrated with several examples of outliers in real-world scenarios.
Chen Chang Lew, Christof Ferreira Torres, et al.
EuroS&P 2024
Jeffrey Burdges, Luca De Feo
Eurocrypt 2021
Jiacen Xu, Xiaokui Shu, et al.
S&P 2024
Balaji Ganesan, Hima Patel, et al.
NeurIPS 2020