162,050 research outputs found
INCORPORATING DIGITAL ETHICS THROUGHOUT THE SOFTWARE DEVELOPMENT PROCESS
The media is reporting scandals associated with computer companies with increasing regularity; whether it is the misuse of user data, breach of privacy concerns, the use of biased artificial intelligence, or the problems of automated vehicles. Because of these complex issues, there is a growing need to equip computer science students with a deep appreciation of ethics, and to ensure that in the future they will develop computer systems that are ethically-based. One particularly useful strand of their education to incorporate ethics into is when teaching them about the formal approaches to developing computer systems.
There are a number of specific processes and methodologies that incorporate these stages in different ways into their approaches. Some take a linear approach to these stages, whereas others take a more iterative and/or incremental approach. These models include the Waterfall Model, the V-Model, the Spiral Model, and the Agile family of models. For each of these models this paper will present a way to include ethics in the Specifying stage, and well as threaded throughout the model, and as an explicit stage in a final review process at the end of the implementation stage.
These formal models are understood (and used) by computer companies all over the world, and therefore are a natural means of incorporating ethics into software development in a manner that would not seem overly arduous or unwieldy to developers. These techniques are also taught in the computer science departments of universities all over the world, it is therefore vitally important that lecturers incorporate an ethical dimension into their systems development teaching, and we believe that these newly refined models provide them with a simple means of achieving this task, and this will make a new generation of software developers ethically-aware
Middleware Technologies for Cloud of Things - a survey
The next wave of communication and applications rely on the new services
provided by Internet of Things which is becoming an important aspect in human
and machines future. The IoT services are a key solution for providing smart
environments in homes, buildings and cities. In the era of a massive number of
connected things and objects with a high grow rate, several challenges have
been raised such as management, aggregation and storage for big produced data.
In order to tackle some of these issues, cloud computing emerged to IoT as
Cloud of Things (CoT) which provides virtually unlimited cloud services to
enhance the large scale IoT platforms. There are several factors to be
considered in design and implementation of a CoT platform. One of the most
important and challenging problems is the heterogeneity of different objects.
This problem can be addressed by deploying suitable "Middleware". Middleware
sits between things and applications that make a reliable platform for
communication among things with different interfaces, operating systems, and
architectures. The main aim of this paper is to study the middleware
technologies for CoT. Toward this end, we first present the main features and
characteristics of middlewares. Next we study different architecture styles and
service domains. Then we presents several middlewares that are suitable for CoT
based platforms and lastly a list of current challenges and issues in design of
CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268,
Digital Communications and Networks, Elsevier (2017
Middleware Technologies for Cloud of Things - a survey
The next wave of communication and applications rely on the new services
provided by Internet of Things which is becoming an important aspect in human
and machines future. The IoT services are a key solution for providing smart
environments in homes, buildings and cities. In the era of a massive number of
connected things and objects with a high grow rate, several challenges have
been raised such as management, aggregation and storage for big produced data.
In order to tackle some of these issues, cloud computing emerged to IoT as
Cloud of Things (CoT) which provides virtually unlimited cloud services to
enhance the large scale IoT platforms. There are several factors to be
considered in design and implementation of a CoT platform. One of the most
important and challenging problems is the heterogeneity of different objects.
This problem can be addressed by deploying suitable "Middleware". Middleware
sits between things and applications that make a reliable platform for
communication among things with different interfaces, operating systems, and
architectures. The main aim of this paper is to study the middleware
technologies for CoT. Toward this end, we first present the main features and
characteristics of middlewares. Next we study different architecture styles and
service domains. Then we presents several middlewares that are suitable for CoT
based platforms and lastly a list of current challenges and issues in design of
CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268,
Digital Communications and Networks, Elsevier (2017
Mobile recommender apps with privacy management for accessible and usable technologies
The paper presents the preliminary results of an ongoing survey of the use of computers and mobile devices, interest in recommender apps and knowledge and concerns about privacy issues amongst English and Italian speaking disabled people. Participants were found to be regular users of computers and mobile devices for a range of applications. They were interested in recommender apps for household items, computer software and apps that met their accessibility and other requirements. They showed greater concerns about controlling access to personal data of different types than this data being retained by the computer or mobile device. They were also willing to make tradeoffs to improve device performance
Context Aware Computing for The Internet of Things: A Survey
As we are moving towards the Internet of Things (IoT), the number of sensors
deployed around the world is growing at a rapid pace. Market research has shown
a significant growth of sensor deployments over the past decade and has
predicted a significant increment of the growth rate in the future. These
sensors continuously generate enormous amounts of data. However, in order to
add value to raw sensor data we need to understand it. Collection, modelling,
reasoning, and distribution of context in relation to sensor data plays
critical role in this challenge. Context-aware computing has proven to be
successful in understanding sensor data. In this paper, we survey context
awareness from an IoT perspective. We present the necessary background by
introducing the IoT paradigm and context-aware fundamentals at the beginning.
Then we provide an in-depth analysis of context life cycle. We evaluate a
subset of projects (50) which represent the majority of research and commercial
solutions proposed in the field of context-aware computing conducted over the
last decade (2001-2011) based on our own taxonomy. Finally, based on our
evaluation, we highlight the lessons to be learnt from the past and some
possible directions for future research. The survey addresses a broad range of
techniques, methods, models, functionalities, systems, applications, and
middleware solutions related to context awareness and IoT. Our goal is not only
to analyse, compare and consolidate past research work but also to appreciate
their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201
Exploratory Study of the Privacy Extension for System Theoretic Process Analysis (STPA-Priv) to elicit Privacy Risks in eHealth
Context: System Theoretic Process Analysis for Privacy (STPA-Priv) is a novel
privacy risk elicitation method using a top down approach. It has not gotten
very much attention but may offer a convenient structured approach and
generation of additional artifacts compared to other methods. Aim: The aim of
this exploratory study is to find out what benefits the privacy risk
elicitation method STPA-Priv has and to explain how the method can be used.
Method: Therefore we apply STPA-Priv to a real world health scenario that
involves a smart glucose measurement device used by children. Different kinds
of data from the smart device including location data should be shared with the
parents, physicians, and urban planners. This makes it a sociotechnical system
that offers adequate and complex privacy risks to be found. Results: We find
out that STPA-Priv is a structured method for privacy analysis and finds
complex privacy risks. The method is supported by a tool called XSTAMPP which
makes the analysis and its results more profound. Additionally, we learn that
an iterative application of the steps might be necessary to find more privacy
risks when more information about the system is available later. Conclusions:
STPA-Priv helps to identify complex privacy risks that are derived from
sociotechnical interactions in a system. It also outputs privacy constraints
that are to be enforced by the system to ensure privacy.Comment: author's post-prin
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