IDS research still needs to strengthen mathematical foundations and theoretic guidelines. In this paper, we build a formal framework, based on information theory, for analyzing and...
Guofei Gu, Prahlad Fogla, David Dagon, Wenke Lee, ...
We propose a framework for quantitative security analysis of machine learning methods. Key issus of this framework are a formal specification of the deployed learning model and a...
The UCLA Parallel Particle-in-Cell (UPIC) Framework, is designed to provide trusted components for building a variety of parallel Particle-in-Cell (PIC) codes. It is based on the ...
This paper presents a Feedback Control real-time Scheduling (FCS) framework for adaptive realtime systems. An advantage of the FCS framework is its use of feedback control theory ...
Chenyang Lu, John A. Stankovic, Sang Hyuk Son, Gan...
In this paper we argue that maximum expected utility is a suitable framework for modeling a broad range of decision problems arising in pattern recognition and related fields. Exa...