| 1. |
- Hatamian, Majid, et al.
(author)
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“It’s shocking!" : Analysing the impact and reactions to the A3: Android apps behaviour analyser
- 2018
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In: Data and Applications Security and Privacy XXXII. - Cham : Springer. - 9783319957289 ; , s. 198-215
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Conference paper (peer-reviewed)abstract
- The lack of privacy awareness in smartphone ecosystems prevents users from being able to compare apps in terms of privacy and from making informed privacy decisions. In this paper we analysed smartphone users’ privacy perceptions and concerns based on a novel privacy enhancing tool called Android Apps Behaviour Analyser (A3). The A3 tool enables user to behaviourally analyse the privacy aspects of their installed apps and notifies about potential privacy invasive activities. To examine the capabilities of A3 we designed a user study. We captured and contrasted privacy concern and perception of 52 participants, before and after using our tool. The results showed that A3 enables users to easily detect their smartphone app’s privacy violation activities. Further, we found that there is a significant difference between users’ privacy concern and expectation before and after using A3 and the majority of them were surprised to learn how often their installed apps access personal resources. Overall, we observed that the A3 tool was capable to influence the participants’ attitude towards protecting their privacy.
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| 2. |
- Hogan, Aidan, et al.
(author)
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Knowledge Graphs
- 2021
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In: ACM Computing Surveys. - : ASSOC COMPUTING MACHINERY. - 0360-0300 .- 1557-7341. ; 54:4
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Journal article (peer-reviewed)abstract
- In this article, we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data. After some opening remarks, we motivate and contrast various graph-based data models, as well as languages used to query and validate knowledge graphs. We explain how knowledge can be represented and extracted using a combination of deductive and inductive techniques. We conclude with high-level future research directions for knowledge graphs.
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| 3. |
- Hogan, Aidan, et al.
(author)
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Knowledge Graphs
- 2021
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Book (other academic/artistic)abstract
- This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale.The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve.This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.
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| 4. |
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| 5. |
- Kampik, Timotheus, 1989-, et al.
(author)
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Governance of autonomous agents on the web : challenges and opportunities
- 2022
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In: ACM Transactions on Internet Technology. - : Association for Computing Machinery (ACM). - 1533-5399 .- 1557-6051. ; 22:4
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Journal article (peer-reviewed)abstract
- The study of autonomous agents has a long tradition in the Multiagent Systems and the Semantic Web communities, with applications ranging from automating business processes to personal assistants. More recently, the Web of Things (WoT), which is an extension of the Internet of Things (IoT) with metadata expressed in Web standards, and its community provide further motivation for pushing the autonomous agents research agenda forward. Although representing and reasoning about norms, policies and preferences is crucial to ensuring that autonomous agents act in a manner that satisfies stakeholder requirements, normative concepts, policies and preferences have yet to be considered as first-class abstractions in Web-based multiagent systems. Towards this end, this paper motivates the need for alignment and joint research across the Multiagent Systems, Semantic Web, and WoT communities, introduces a conceptual framework for governance of autonomous agents on the Web, and identifies several research challenges and opportunities.
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| 6. |
- Kampik, Timotheus, 1989-, et al.
(author)
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Norms and Policies for Agents on the Web
- 2021
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In: Autonomous Agents on the Web Dagstuhl (Dagstuhl Seminar 21072). - Germany : Schloss Dagstuhl – Leibniz-Zentrum für Informatik, Dagstuhl Publishing. ; , s. 88-98
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Book chapter (other academic/artistic)abstract
- The study of policies and norms has a long tradition in the Semantic Web & Linked Data and Multi-Agent Systems communities, with applications ranging from business processes, and legal reasoning, to information systems governance. Although representing and reasoning about norms is crucial in ensuring that autonomous agents act in a manner to satisfy stake- holder requirements, normative concepts have yet to be considered as first-class abstractions in Web-based software systems. The chapter motivates the practical need to apply research on policies and norms to autonomous agents on the Web, and highlights research challenges and opportunities at the intersection of the Semantic Web & Linked Data, Multi-Agent Systems, and Web Architecture & Web of Things communities.
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| 7. |
- Reuben, Jenni, 1983-
(author)
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Go the Extra Mile for Accountability : Privacy Protection Measures for Emerging Information Management Systems
- 2020
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Doctoral thesis (other academic/artistic)abstract
- The thesis considers a systematic approach to design and develop techniques for preventing personal data exposure in next generation information management systems with the aim of ensuring accountability of data controllers (entities that process personal data).With a rapid growth in the communication technologies, heterogenous computing environments that offer cost-effective data processing alternatives are emerging. Thus, the information-flow of personal data spans beyond the information processing practices of data controllers thereby involving other parties that process personal data. Moreover, in order to enable interoperability, data in such environments is given well-defined structure and meaning by means of graph-based data models. Graphs, inherently emphasize connections between things, and when graphs are used to model personal data records, the connections and the network structure may reveal intimate details about our inter-connected society.In the European context, the General Data Protection Regulation (GDPR) provides a legal framework for personal data processing. The GDPR stipulates specific consequences for non-compliance to the data protection principles, in the view of ensuring accountability of data controllers in their personal data processing practices. Widely recognized approaches to implement the Privacy by Design (PbD) principle in the software application development process, are broader in scope. Hence, processes to implement personal data protection techniques for specific systems are not the central aspect of the aforementioned approaches.In order to influence the implementation of techniques for preventing personal data misuse associated with sharing of data represented as graphs, a conceptual mechanism for building privacy techniques is developed. The conceptual mechanism consists of three elements, namely, a risk analysis for Semantic Web information management systems using Privacy Impact Assessment (PIA) approach, two privacy protection techniques for graphs enriched with semantics and a model to approach evaluation of adherence to the goals resulted from the risk analysis. The privacy protection techniques include an access control model that embodies purpose limitation principle—an essential aspect of GDPR—and adaptations of the differential privacy model for graphs with edge labels. The access control model takes into account the semantics of the graph elements for authorizing access to the graph data. In our differential privacy adaptations, we define and study through experiments, four different approaches to adapt the differential privacy model to edge-labeled graph datasets.
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