Anomaly detection in IP networks, detection of deviations from what is considered normal, is an important complement to misuse detection based on known attack descriptions. Perfor...
It is often highly valuable for organizations to have their data analyzed by external agents. However, any program that computes on potentially sensitive data risks leaking inform...
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
The integration of data produced and collected across autonomous, heterogeneous web services is an increasingly important and challenging problem. Due to the lack of global identi...
Luis Gravano, Panagiotis G. Ipeirotis, Nick Koudas...
This paper presents a data oriented approach to modeling the complex computing systems, in which an ensemble of correlation models are discovered to represent the system status. I...