1,721,142 research outputs found
Change impact analysis for context-aware applications in intelligent environments
No full textAs software systems for context-aware applications and intelligent environments become increasingly complex and adaptive, the need to understand and predict the impact of changes grows. Such changes may manifest themselves (1) as alterations in the way users behave, (2) as software customizations to handle new requirements, and (3) as variations on the dynamic context in which intelligent environment systems are deployed and operate. Such internal and external changes may be anticipated or unforeseen in nature. With reliability being a key concern for intelligent environments, we revisit in this work the state-of-practice on change impact analysis (CIA) − a well-known methodology in software engineering − and investigate to what extent it can be applied and enhanced to contribute to the development of more reliable context-aware adaptive applications to increase the confidence in intelligent environment systems.status: Publishe
Special Issue: Big Data for Context-Aware Applications and Intelligent Environments
No full textDisruptive paradigm shifts such as the Internet of Things (IoT) and Cyber-Physical Systems (CPS) are creating a wealth of streaming context information. Large-scale context-awareness combining IoT and Big Data drive the creation of smarter application ecosystems in diverse vertical domains, including smart health, finance, smart grids and cities, transportation, Industry 4.0, etc. This special issue addresses core topics on the design, the use and the evaluation of Big Data enabling technologies to build next-generation context-aware applications and computing systems for future intelligent environments.sponsorship: H2020 project EXCELL|691829status: Publishe
Ambient Intelligence - Software and Applications: 2nd International Symposium on Ambient Intelligence (ISAmI 2011)
No full textstatus: Publishe
Revisiting OAuth 2.0 Compliance: A Two-Year Follow-Up Study
No full textOAuth 2.0 is a widely used authorization protocol that allows third-party access to an authorization service on behalf of a user. Like any security protocol, it requires careful implementation to ensure security. Previous research has thoroughly analyzed the security of the OAuth protocol, but popular deployments remain vulnerable due to incorrect or limited implementation of the standards. In our previous work, we introduced a tool called OAuch to measure and improve compliance with the OAuth standards. We used the tool to measure the compliance of 100 OAuth implementations and created a unique overview of the state of practice within the OAuth ecosystem. This paper revisits these prior results and updates our measurements. We compare the latest results to the original baseline and
identify changes in the ecosystem. Our analysis shows that IdPs have become more compliant in the past two years, but a substantial number still lack fundamental countermeasures.sponsorship: This research is partially funded by the Research Fund KU Leuven, the APISEC project, and by the Flemish Research Program Cybersecurity. (Research Fund KU Leuven, Flemish Research Program Cybersecurity)status: Publishe
Introduction to the thematic issue on Intelligent systems, applications and environments for the industry of the future
No full textRecent advances in the area of ubiquitous computing, ambient intelligence and intelligent environments are making inroads in business-oriented application domains. This issue of JAISE addresses core topics on the design, use and evaluation of smart applications and systems for the factory of the future, an emerging trend perhaps better known as Industry 4.0.
The digital transformation in the enterprise envisioned by Industry 4.0 will entwine the cyber-physical world and real world of manufacturing to deliver networked production with enhanced process transparency. Production systems, data analytics and cloud-enabled business processes will interact directly with customers to realize the ambitious goal of single lot individualized manufacturing.
This thematic issue features a survey and 5 research articles which address the modeling, designing, implementation, assessment and management of intelligent systems, applications and environments that will shape and advance the smart industry of the future.sponsorship: The guest editors are also grateful to the European Commission and the H2020 project EXCELL (http://excell-project.eu/) under grant No. 691829 for supporting the guest editors to organize this thematic issue and strengthen scientific awareness in the area of Industry 4.0. (H project EXCELL|691829)status: Publishe
Masterkey attacks against free-text keystroke dynamics and security implications of demographic factors
No full textThis paper presents and systematically evaluates the first masterkey attack against free-text keystroke dynamics. A masterkey is a typing sequence that matches, hence successfully impersonates, a large part of the population. Therefore, masterkeys are effective tools for an adversary who aims to impersonate someone without knowledge of their typing behavior. On top of the attack itself, we present a new unifying evaluation framework for masterkey attacks that allow for the comparison with knowledge-based authentication factors. In other words, we unify the evaluation of password security with that of masterkey attacks and demonstrate that typing biometrics is approximately 20 times less secure than passwords and approximately two times less secure than a 4-digit pin. Lastly, we study the effect of demographics on typing biometrics, which, among others, provides novel insights into the effect of being a well-versed typist on security.sponsorship: Research Fund KU Leuven, Flemish Research Programme Cybersecuritystatus: Publishe
Where people and cars meet: social interactions to improve information sharing in large scale vehicular networks
No full textEfficient delivery of information in vehicular networks is crucial for the creation of useful and usable applications that need to cope with nomadic large-scale environments. Context-awareness is often key to improve efficiency of a vehicle network since it allows to make informed decisions on the data routing, data locality and data necessity for different moving objects. In this paper we show how the social network of vehicle residents, as part of the overall context, allows us to improve the information sharing in the vehicular network signifficantly. We demonstrate this by deploying a social ubiquitous-help-system (UHS) on top of a vehicular network. We analyze how UHS operates in a vehicular network using a network simulation of realistic large scale vehicular movement data and show that the social interactions increases the efficiency, relevance and quality of information in data delivery
Where people and cars meet: social interactions to improve information sharing in large scale vehicular networks
No full textEfficient delivery of information in vehicular networks is crucial for the creation of useful and usable applications that need to cope with nomadic large-scale environments. Context-awareness is often key to improve efficiency of a vehicle network since it allows to make informed decisions on the data routing, data locality and data necessity for different moving objects. In this paper we show how the social network of vehicle residents, as part of the overall context, allows us to improve the information sharing in the vehicular network signifficantly. We demonstrate this by deploying a social ubiquitous-help-system (UHS) on top of a vehicular network. We analyze how UHS operates in a vehicular network using a network simulation of realistic large scale vehicular movement data and show that the social interactions increases the efficiency, relevance and quality of information in data delivery
A DSL for context quality modeling in context-aware applications
No full textDeveloping reliable context-aware applications remains a big
challenge, even after a decade of research in this area. Usually a lot of code is required to handle an application's correct behavior in a variety of different situations. Along with a growing amount of code, also increases the risk of programming errors that may lead to an undesired behavior in particular situations. In this paper we present a domain specific language (DSL) for developing context-aware applications. It allows creating context quality models which are transformed into software artifacts of the final application. This code generation saves time and effort, and helps to ensure an appropriate autonomic behavior at runtime in inherently uncertain situations.status: Publishe
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