Machine learning (ML) techniques have been successfully applied to a wide array of applications. This dissertation aims to take application data handling into account when developing ML-based solutions for real-world problems through a holistic framework. To demonstrate the generality of our framework, we consider two real-world applications: spam…

Digital systems are pervasive in modern societies -- augmenting personal and commercial driving, detecting cancer, and exploiting transitory events in financial markets. Attacks on these systems are growing in number, sophistication, and impact. Current cyber defenses are proving inadequate against some of these attacks. Cyber defense tools that…

The need for detecting malicious behavior on a computer networks continued to be important to maintaining a safe and secure environment. The purpose of this study was to determine the relationship of multilayer feed forward neural network architecture to the ability of detecting abnormal behavior in networks. This involved building, training, and…

The research problem that inspired this effort is the challenge of managing the security of systems in large-scale heterogeneous networked environments. Human intervention is slow and limited: humans operate at much slower speeds than networked computer communications and there are few humans associated with each network. Enabling each node in the…