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

Design and evaluation of an architecture for future smart grid service provisioning

In recent years, there has been a growing interest in cloud technologies. Using current cloud solutions, it is however difficult to create customizable multi-tenant applications, especially if the application must support varying Quality of Service (QoS) guarantees. Software Product Line Engineering (SPLE) and feature modeling techniques are commonly used to address these issues in non-cloud applications, but these techniques cannot be ported directly to a cloud context, as the common approaches are geared towards customization of on-premise deployed applications, and do not support multi-tenancy. In this paper, we propose an architecture for the development and management of customizable Software as a Service (SaaS) applications, built using SPLE techniques. In our approach, each application is a composition of services, where individual services correspond to specific application functionalities, referred to as features. A feature-based methodology is described to abstract and convert the application information required at different stages of the application life-cycle: development, customization and deployment. We specifically focus on how development feature models can be adapted ensuring a one-to-one correspondence between features and services exists, ensuring the composition of services yields an application containing the corresponding features. These runtime features can then be managed using feature placement techniques. The proposed approach enables developers to define significantly less features, while limiting the amount of automatically generated features in the application runtime stage. Conversion times between models are shown to be in the order of milliseconds, while execution times of management algorithms are shown to improve by 5 to 17% depending on the application case

A Case Study on Academic Services Application Using Agile Methodology for Mobile Cloud Computing

Recently, Mobile Cloud Computing reveals many modern development areas in the Information Technology industry. Several software engineering frameworks and methodologies have been developed to provide solutions for deploying cloud computing resources on mobile application development. Agile methodology is one of the most commonly used methodologies in the field. This paper presents the MCCAS a Web and Mobile application that provide feature for the Palestinian higher education/academic institutions. An Agile methodology was used in the development of the MCCAS but in parallel with emphasis on Cloud computing resources deployment. Also many related issues is discussed such as how software engineering modern methodologies (advances) influenced the development process

Model-driven Engineering IDE for Quality Assessment of Data-intensive Applications

This article introduces a model-driven engineering (MDE) integrated development environment (IDE) for Data-Intensive Cloud Applications (DIA) with iterative quality enhancements. As part of the H2020 DICE project (ICT-9-2014, id 644869), a framework is being constructed and it is composed of a set of tools developed to support a new MDE methodology. One of these tools is the IDE which acts as the front-end of the methodology and plays a pivotal role in integrating the other tools of the framework. The IDE enables designers to produce from the architectural structure of the general application along with their properties and QoS/QoD annotations up to the deployment model. Administrators, quality assurance engineers or software architects may also run and examine the output of the design and analysis tools in addition to the designer in order to assess the DIA quality in an iterative process

Designing and implementing a GPS-based vehicle navigation application for Eclipse Kuksa

Abstract. With the development of the Internet of Things (IoT), connected cars are rapidly becoming an essential milestone in the design of intelligent transportation systems and a key element in smart city design. Connected cars use a three-layer client-connection-cloud architecture, and car sensors are located at the client layer. This architecture provides the driver with a large amount of data about the external environment, which reduces the number of traffic accidents and helps the car drive safely. Driving safety is the most critical design factor for next-generation vehicles. The future vision of the automotive industry is self-driving cars. However, it faces some challenges. Eclipse Kuksa provides solutions to challenges in the field of connected cars. A comprehensive ecosystem includes a complete tool stack for connected vehicles, including a vehicle platform, a cloud platform, and an application development Integrated Development Environment (IDE). Its essential function is to collect, store, and analyze vehicle data and transmit various information in the cloud. This master’s thesis aims to investigate a Global Positioning System (GPS) -based vehicle navigation application on the vehicle and cloud platforms of Eclipse Kuksa, understand how to develop a GPS-based vehicle navigation application using the Eclipse Kuksa software platform, and discuss the advantages and challenges of using Eclipse Kuksa to develop vehicle applications. The research methods are Design Science Research (DSR) and literature review. System development is carried out following the Design Science Research Methodology (DSRM) Process, developed and evaluated on the vehicle navigation application. The application artifact consists of the Eclipse Kuksa vehicle platform and cloud platform. The steps described in this paper can be used to build vehicle applications in Eclipse Kuksa. This paper also explains the benefits and challenges of using Eclipse Kuksa to develop vehicle applications. The main benefit is that open source solutions break the long-term closed development model of the automotive industry and establish a vehicle-to-cloud solution standard to meet the IoT challenges to the automotive industry. Simultaneously the challenge of using Eclipse Kuksa is the complexity of environment construction and the software and hardware compatibility

A case study in open source innovation: developing the Tidepool Platform for interoperability in type 1 diabetes management.

OBJECTIVE:Develop a device-agnostic cloud platform to host diabetes device data and catalyze an ecosystem of software innovation for type 1 diabetes (T1D) management. MATERIALS AND METHODS:An interdisciplinary team decided to establish a nonprofit company, Tidepool, and build open-source software. RESULTS:Through a user-centered design process, the authors created a software platform, the Tidepool Platform, to upload and host T1D device data in an integrated, device-agnostic fashion, as well as an application ("app"), Blip, to visualize the data. Tidepool's software utilizes the principles of modular components, modern web design including REST APIs and JavaScript, cloud computing, agile development methodology, and robust privacy and security. DISCUSSION:By consolidating the currently scattered and siloed T1D device data ecosystem into one open platform, Tidepool can improve access to the data and enable new possibilities and efficiencies in T1D clinical care and research. The Tidepool Platform decouples diabetes apps from diabetes devices, allowing software developers to build innovative apps without requiring them to design a unique back-end (e.g., database and security) or unique ways of ingesting device data. It allows people with T1D to choose to use any preferred app regardless of which device(s) they use. CONCLUSION:The authors believe that the Tidepool Platform can solve two current problems in the T1D device landscape: 1) limited access to T1D device data and 2) poor interoperability of data from different devices. If proven effective, Tidepool's open source, cloud model for health data interoperability is applicable to other healthcare use cases

Co-transformation to cloud-native applications : development experiences and experimental evaluation

Modern software applications following cloud-native design principles and architecture guidelines have inherent advantages in fulfilling current user requirements when executed in complex scheduled environments. Engineers responsible for software applications therefore have an intrinsic interest to migrate to cloud-native architectures. Existing methodologies for transforming legacy applications do not yet consider migration from partly cloud-enabled and cloud-aware applications under continuous development. This work thus introduces a co-transformation methodology and validates it through the migration of a prototypical music identification and royalty collection application. Experimental results demonstrate that the proposed methodology is capable to effectively guide a transformation process, resulting in elastic and resilient cloud-native applications. Findings include the necessity to maintain application self-management even on modern cloud platforms