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Computers, Volume 2, Issue 1 (March 2013) – 2 articles , Pages 1-66

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Article
Architecture and Knowledge-Driven Self-Adaptive Security in Smart Space
by Antti Evesti, Jani Suomalainen and Eila Ovaska
Computers 2013, 2(1), 34-66; https://doi.org/10.3390/computers2010034 - 18 Mar 2013
Cited by 18 | Viewed by 10396
Abstract
Dynamic and heterogeneous smart spaces cause challenges for security because it is impossible to anticipate all the possible changes at design-time. Self-adaptive security is an applicable solution for this challenge. This paper presents an architectural approach for security adaptation in smart spaces. The [...] Read more.
Dynamic and heterogeneous smart spaces cause challenges for security because it is impossible to anticipate all the possible changes at design-time. Self-adaptive security is an applicable solution for this challenge. This paper presents an architectural approach for security adaptation in smart spaces. The approach combines an adaptation loop, Information Security Measuring Ontology (ISMO) and a smart space security-control model. The adaptation loop includes phases to monitor, analyze, plan and execute changes in the smart space. The ISMO offers input knowledge for the adaptation loop and the security-control model enforces dynamic access control policies. The approach is novel because it defines the whole adaptation loop and knowledge required in each phase of the adaptation. The contributions are validated as a part of the smart space pilot implementation. The approach offers reusable and extensible means to achieve adaptive security in smart spaces and up-to-date access control for devices that appear in the space. Hence, the approach supports the work of smart space application developers. Full article
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A User-Centric View of Intelligent Environments: User Expectations, User Experience and User Role in Building Intelligent Environments
by Eija Kaasinen, Tiina Kymäläinen, Marketta Niemelä, Thomas Olsson, Minni Kanerva and Veikko Ikonen
Computers 2013, 2(1), 1-33; https://doi.org/10.3390/computers2010001 - 27 Dec 2012
Cited by 40 | Viewed by 12495
Abstract
Our everyday environments are gradually becoming intelligent, facilitated both by technological development and user activities. Although large-scale intelligent environments are still rare in actual everyday use, they have been studied for quite a long time, and several user studies have been carried out. [...] Read more.
Our everyday environments are gradually becoming intelligent, facilitated both by technological development and user activities. Although large-scale intelligent environments are still rare in actual everyday use, they have been studied for quite a long time, and several user studies have been carried out. In this paper, we present a user-centric view of intelligent environments based on published research results and our own experiences from user studies with concepts and prototypes. We analyze user acceptance and users’ expectations that affect users’ willingness to start using intelligent environments and to continue using them. We discuss user experience of interacting with intelligent environments where physical and virtual elements are intertwined. Finally, we touch on the role of users in shaping their own intelligent environments instead of just using ready-made environments. People are not merely “using” the intelligent environments but they live in them, and they experience the environments via embedded services and new interaction tools as well as the physical and social environment. Intelligent environments should provide emotional as well as instrumental value to the people who live in them, and the environments should be trustworthy and controllable both by regular users and occasional visitors. Understanding user expectations and user experience in intelligent environments, and providing users with tools to influence the environments can help to shape the vision of intelligent environments into meaningful, acceptable and appealing service entities for all those who live and act in them. Full article
(This article belongs to the Special Issue Large Scale Intelligent Environments)
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