Advanced Cloud Privacy Threat Modeling

Privacy-preservation for sensitive data has become a challenging issue in cloud computing. Threat modeling as a part of requirements engineering in secure software development provides a structured approach for identifying attacks and proposing countermeasures against the exploitation of vulnerabilities in a system . This paper describes an extension of Cloud Privacy Threat Modeling (CPTM) methodology for privacy threat modeling in relation to processing sensitive data in cloud computing environments. It describes the modeling methodology that involved applying Method Engineering to specify characteristics of a cloud privacy threat modeling methodology, different steps in the proposed methodology and corresponding products. We believe that the extended methodology facilitates the application of a privacy-preserving cloud software development approach from requirements engineering to design

Addressing challenges to teach traditional and agile project management in academia

In order to prepare students for a professional IT career, most universities attempt to provide a current educational curriculum in the Project Management (PM) area to their students. This is usually based on the most promising methodologies used by the software industry. As instructors, we need to balance traditional methodologies focused on proven project planning and control processes leveraging widely accepted methods and tools along with the newer agile methodologies. Such new frameworks emphasize that software delivery should be done in a flexible and iterative manner and with significant collaboration with product owners and customers. In our experience agile methodologies have witnessed an exponential growth in many diverse software organizations, and the various agile PM tools and techniques will continue to see an increase in adoption in the software development sector. Reflecting on these changes, there is a critical need to accommodate best practices and current methodologies in our courses that deliver Project Management content. In this paper we analyse two of the most widely used methodologies for traditional and agile software development – the widely used ISO/PMBOK standard provided by the Project Management Institute and the well-accepted Scrum framework. We discuss how to overcome curriculum challenges and deliver a quality undergraduate PM course for a Computer Science and Information systems curricula. Based on our teaching experience in Europe and North America, we present a comprehensive comparison of the two approaches. Our research covers the main concepts, processes, and roles associated with the two PM frameworks and recommended learning outcomes. The paper should be of value to instructors who are keen to see their computing students graduate with a sound understanding of current PM methodologies and who can deliver real-world software products.Accepted manuscrip

An Adaptive Design Methodology for Reduction of Product Development Risk

Embedded systems interaction with environment inherently complicates understanding of requirements and their correct implementation. However, product uncertainty is highest during early stages of development. Design verification is an essential step in the development of any system, especially for Embedded System. This paper introduces a novel adaptive design methodology, which incorporates step-wise prototyping and verification. With each adaptive step product-realization level is enhanced while decreasing the level of product uncertainty, thereby reducing the overall costs. The back-bone of this frame-work is the development of Domain Specific Operational (DOP) Model and the associated Verification Instrumentation for Test and Evaluation, developed based on the DOP model. Together they generate functionally valid test-sequence for carrying out prototype evaluation. With the help of a case study 'Multimode Detection Subsystem' the application of this method is sketched. The design methodologies can be compared by defining and computing a generic performance criterion like Average design-cycle Risk. For the case study, by computing Average design-cycle Risk, it is shown that the adaptive method reduces the product development risk for a small increase in the total design cycle time.Comment: 21 pages, 9 figure

Stochastic-Based Pattern Recognition Analysis

In this work we review the basic principles of stochastic logic and propose its application to probabilistic-based pattern-recognition analysis. The proposed technique is intrinsically a parallel comparison of input data to various pre-stored categories using Bayesian techniques. We design smart pulse-based stochastic-logic blocks to provide an efficient pattern recognition analysis. The proposed rchitecture is applied to a specific navigation problem. The resulting system is orders of magnitude faster than processor-based solutions