7,331 research outputs found
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Animal-Computer Interaction: a Manifesto (2011) and sections from Towards an Animal-Centred Ethics for Animal-Computer Interaction (2016)
Reprint of journal article "Animal-Computer Interaction: a Manifesto" (2011) and of sections of journal article "Towards an Animal-Centred Ethics for Animal-Computer Interaction" (2016
Management and Service-aware Networking Architectures (MANA) for Future Internet Position Paper: System Functions, Capabilities and Requirements
Future Internet (FI) research and development threads have recently been gaining momentum all over the world and as such the international race to create a new generation Internet is in full swing: GENI, Asia Future Internet, Future Internet Forum Korea, European Union Future Internet Assembly (FIA). This is a position paper identifying the research orientation with a time horizon of 10 years, together with the key challenges for the capabilities in the Management and Service-aware Networking Architectures (MANA) part of the Future Internet (FI) allowing for parallel and federated Internet(s)
Protocol for a Systematic Literature Review on Security-related Research in Ubiquitous Computing
Context: This protocol is as a supplementary document to our review paper that investigates security-related challenges and solutions that have occurred during the past decade (from January 2003 to December 2013).
Objectives: The objective of this systematic review is to identify security-related challenges, security goals and defenses in ubiquitous computing by answering to three main research questions. First, demographic data and trends will be given by analyzing where, when and by whom the research has been carried out. Second, we will identify security goals that occur in ubiquitous computing, along with attacks, vulnerabilities and threats that have motivated the research. Finally, we will examine the differences in addressing security in ubiquitous computing with those in traditional distributed systems.
Method: In order to provide an overview of security-related challenges, goals and solutions proposed in the literature, we will use a systematic literature review (SLR). This protocol describes the steps which are to be taken in order to identify papers relevant to the objective of our review. The first phase of the method includes planning, in which we define the scope of our review by identifying the main research questions, search procedure, as well as inclusion and exclusion criteria. Data extracted from the relevant papers are to be used in the second phase of the method, data synthesis, to answer our research questions. The review will end by reporting on the results.
Results and conclusions: The expected results of the review should provide an overview of attacks, vulnerabilities and threats that occur in ubiquitous computing and that have motivated the research in the last decade. Moreover, the review will indicate which security goals are gaining on their significance in the era of ubiquitous computing and provide a categorization of the security-related countermeasures, mechanisms and techniques found in the literature. (authors' abstract)Series: Working Papers on Information Systems, Information Business and Operation
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SocialFusion: Context-Aware Inference and Recommendation By Fusing Mobile, Sensor, and Social Data ; CU-CS-1059-09
When Things Matter: A Data-Centric View of the Internet of Things
With the recent advances in radio-frequency identification (RFID), low-cost
wireless sensor devices, and Web technologies, the Internet of Things (IoT)
approach has gained momentum in connecting everyday objects to the Internet and
facilitating machine-to-human and machine-to-machine communication with the
physical world. While IoT offers the capability to connect and integrate both
digital and physical entities, enabling a whole new class of applications and
services, several significant challenges need to be addressed before these
applications and services can be fully realized. A fundamental challenge
centers around managing IoT data, typically produced in dynamic and volatile
environments, which is not only extremely large in scale and volume, but also
noisy, and continuous. This article surveys the main techniques and
state-of-the-art research efforts in IoT from data-centric perspectives,
including data stream processing, data storage models, complex event
processing, and searching in IoT. Open research issues for IoT data management
are also discussed
What goes in, must come out:combining scat-based molecular diet analysis and quantification of ingested microplastics in a marine top predator
Context: Microplastics (plastic particles <5 mm in size) are highly available for ingestion by a wide range of organisms, either through direct consumption or indirectly, via trophic transfer, from prey to predator. The latter is a poorly understood, but potentially major, route of microplastic ingestion for marine top predators.Approach: We developed a novel and effective methodology pipeline to investigate dietary exposure of wild top predators (grey seals; Halichoerus grypus) to microplastics, by combining scat-based molecular techniques with a microplastic isolation method. We employed DNA metabarcoding, a rapid method of biodiversity assessment, to garner detailed information on prey composition from scats, and investigated the potential relationship between diet and microplastic burden.Results: Outcomes of the method development process and results of both diet composition from metabarcoding analysis and detection of microplastics are presented. Importantly, the pipeline performed well and initial results suggest the frequency of microplastics detected in seal scats may be related to the type of prey consumed. Conclusions: Our non-invasive, data rich approach maximises time and resource-efficiency, while minimising costs and sample volumes required for analysis. This pipeline could be used to underpin a much-needed increase in understanding of the relationship between diet composition and rates of microplastic ingestion in high trophic-level species.<br/
ConXsense - Automated Context Classification for Context-Aware Access Control
We present ConXsense, the first framework for context-aware access control on
mobile devices based on context classification. Previous context-aware access
control systems often require users to laboriously specify detailed policies or
they rely on pre-defined policies not adequately reflecting the true
preferences of users. We present the design and implementation of a
context-aware framework that uses a probabilistic approach to overcome these
deficiencies. The framework utilizes context sensing and machine learning to
automatically classify contexts according to their security and privacy-related
properties. We apply the framework to two important smartphone-related use
cases: protection against device misuse using a dynamic device lock and
protection against sensory malware. We ground our analysis on a sociological
survey examining the perceptions and concerns of users related to contextual
smartphone security and analyze the effectiveness of our approach with
real-world context data. We also demonstrate the integration of our framework
with the FlaskDroid architecture for fine-grained access control enforcement on
the Android platform.Comment: Recipient of the Best Paper Awar
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