Justin M. Beaver

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A barrier to the widespread adoption of learning-based network intrusion detection tools is the in-situ training requirements for effective discrimination of malicious traffic. Supervised learning techniques necessitate a quantity of labeled examples that is often intractable, and at best cost-prohibitive. Recent advances in semi-supervised techniques have(More)
The ability to reliably predict the end quality of software under development presents a significant advantage for a development team. It provides an opportunity to address high risk components earlier in the development life cycle, when their impact is minimized. This research proposes a model that captures the evolution of the quality of a software(More)
Power system disturbances are inherently complex and can be attributed to a wide range of sources, including both natural and man-made events. Currently, the power system operators are heavily relied on to make decisions regarding the causes of experienced disturbances and the appropriate course of action as a response. In the case of cyber-attacks against(More)
Critical infrastructure Supervisory Control and Data Acquisition (SCADA) systems have been designed to operate on closed, proprietary networks where a malicious insider posed the greatest threat potential. The centralization of control and the movement towards open systems and standards has improved the efficiency of industrial control, but has also exposed(More)
Modern enterprises are becoming increasingly sensitive to the potential destructive power of small groups or individuals with malicious intent. In response, significant investments are being made in developing a means to assess the likelihood of certain threats to their enterprises. Threat assessment needs are typically focused in very specific application(More)
Effective visual analysis of computer network defense (CND) information is challenging due to the volume and complexity of both the raw and analyzed network data. A typical CND is comprised of multiple niche intrusion detection tools, each of which performs network data analysis and produces a unique alerting output. The state-of-the-practice in the(More)
A significant challenge in software engineering is accurately modeling projects in order to correctly forecast success or failure. The primary difficulty is that software development efforts are complex in terms of both the technical and social aspects of the engineering environment. This is compounded by the lack of real data that captures both the(More)
Modern computer network defense systems rely primarily on signature-based intrusion detection tools, which generate alerts when patterns that are pre-determined to be malicious are encountered in network data streams. Signatures are created reactively, and only after in-depth manual analysis of a network intrusion. There is little ability for(More)
This paper provides an analysis of the effect of the skill/experience of the software development team on the quality of the final software product. A method for the assessment of software development team skill and experience is proposed, and was derived from a workforce management tool currently in use by the National Aeronautics and Space Administration.(More)
The stigmergy collaboration approach provides a hypothesized explanation about how online groups work together. In this research, we presented a stigmergy approach for building an agent based open source software (OSS) developer community collaboration simulation. We used group of actors who collaborate on OSS projects as our frame of reference and(More)