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Knowledge Graph Driven Human-Friendly Information Security

Project Description

Knowledge Graph [1,2] is regarded as a disruptive technology that combines Big Data and Semantic technologies to support knowledge management inside organisations. It helps provide more transparency and openness into organisations, so as to empowers individuals to share knowledge and to make decisions based on comprehensive knowledge. On the one hand, this could help unleash human potential; on the other hand, it will enable human to share understanding with machines and programs. In this project, we will look into the impact of Knowledge Graph on information security and privacy, in particular on social / human factors [3].

During the project, the student will also be supervised on the methodology of scientific research, experimenting, writing, presenting, team-working. To support the project, the student will be able to collaborate with world leading industries related on semantic technologies.

The successful candidate should have, or expect to have, an Honours Degree at 2.1 or above (or equivalent) in Computer Science, Mathematics, Engineering, Data Science or related disciplines.

Essential Background: Computer science or Artificial Intelligence.

Knowledge of: It is essential for the student to have solid knowledge of one of the following disciplines of modern computer science and artificial intelligence: discrete mathematics, knowledge-based systems, cloud computing. It is important for the student to have a basic understanding of modern database systems and distributed systems. The student should have good programming skills.

Funding Notes

There is no funding attached to this project, it is for self-funded students only


[1] Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez Perez and Honghan Wu (Eds.). Exploiting Linked Data and Knowledge Graphs for Large Organisations. ISBN 978-3-319-45652-2, Springer, 2016.

[2] Jeff Z. Pan, Diego Calvanese, Thomas Eiter, Ian Horrocks, Michael Kifer, Fangzhen Lin and Yuting Zhao (Eds.). Reasoning Web: Logical Foundation of Knowledge Graph Construction and Querying Answering. ISBN 978-3-319-49492-0, Springer, 2017.

[3] John Paul Vargheese, Peter Travers, Jeff Z. Pan, Kathryn Vincent, Claire Wallace and Anna Kabedeva. Constructing Social Media Knowledge Graphs with Social Scientists. In Proc. of the 30th 30th British Human Computer Interaction Conference (HCI2016), 2016. (Slides: http://www.slideshare.net/jeffpan_sw/constructing-social-media-knowledge-graphs-with-social-scientists)

This project is advertised in relation to the research areas of the discipline of Computing Science. Formal applications can be completed online: http://www.abdn.ac.uk/postgraduate/apply. You should apply for PhD in Computing Science, to ensure that your application is passed to the correct College for processing. NOTE CLEARLY THE NAME OF THE SUPERVISOR and EXACT PROJECT TITLE ON THE APPLICATION FORM.Applicants are limited to applying for a maximum of 2 projects. Any further applications received will be automatically withdrawn.

Informal inquiries can be made to Dr J Pan ([email protected]) with a copy of your curriculum vitae and cover letter. All general enquiries should be directed to the Graduate School Admissions Unit ([email protected]).

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