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  Privacy-preserving Systems around Security, Trust and Identity


   School of Computing, Engineering & the Built Environment

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  Dr Pavlos Papadopoulos, Prof B Buchanan, Dr NIKOLAOS Pitropakis  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

Blockpass and the School of Computing at Edinburgh Napier University have set up an advanced Blockchain Identity Lab (BIL), which aims to support world-leading research related to cryptography, blockchain, distributed ledger technologies, privacy-preserving machine learning, and their linkage to sovereign identities such as decentralised identities and verifiable credentials. It currently supports several PhD studentships, and due to the successful commercialisation of its work, it aims to increase this number. Successful applicants in this role will investigate, but are not limited to, a wide range of areas related to security, privacy, identity, trust/consent/delegation, and secure software development processes. A key focus will be on privacy-preserving methods, trusted smart contracts, anonymised machine learning, and the integration of trust, governance and consent around distributed models.

Academic qualifications

A first-class honours degree, or a distinction at master level, or equivalent achievements ideally in Computer Science with a good fundamental knowledge of computer science and computer security.

English language requirement

IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available online. 

Application process

Prospective applicants are encouraged to contact the supervisor Dr Pavlos Papadopoulos at [Email Address Removed] to discuss the content of the project and the fit with their qualifications and skills before preparing an application. 

The application must include: 

Research project outline of 2 pages (list of references excluded) with the details about: 

  • Background and motivation of the project. The motivation must be supported by relevant literature. You can discuss also the applications you expect for the project results. 
  • Research questions or objectives. 
  • Methodology: types of data to be used, approach to data collection, and data analysis methods 
  • List of references 

Statement no longer than 1 page describing your motivations and fit with the project.

Recent and complete curriculum vitae. 

Two academic references (but if you have been out of education for more than three years, you may submit one academic and one professional reference), the form can be downloaded here

Documents proving your qualifications and your skills. 

Applications can be submitted here. To be considered, the application must use: 

  • “SCEBE0523” as project code. 
  • the advertised title as project title  

All applications must be received by 21st May 2023 and include the required documents. Applicants who have not been contacted by 1 month later should assume that they have been unsuccessful.

Computer Science (8)

References

Bernabe, J. B., Canovas, J. L., Hernandez-Ramos, J. L., Moreno, R. T., & Skarmeta, A. (2019). Privacy-preserving solutions for blockchain: Review and challenges. IEEE Access, 7, 164908-164940.
Androulaki, E., Barger, A., Bortnikov, V., Cachin, C., Christidis, K., De Caro, A., ... & Yellick, J. (2018, April). Hyperledger fabric: a distributed operating system for permissioned blockchains. In Proceedings of the thirteenth EuroSys conference (pp. 1-15).
Yin, X., Zhu, Y., & Hu, J. (2021). A comprehensive survey of privacy-preserving federated learning: A taxonomy, review, and future directions. ACM Computing Surveys (CSUR), 54(6), 1-36.
Mohammed, N. M., Niazi, M., Alshayeb, M., & Mahmood, S. (2017). Exploring software security approaches in software development lifecycle: A systematic mapping study. Computer Standards & Interfaces, 50, 107-115.
Corallo, A., Lazoi, M., & Lezzi, M. (2020). Cybersecurity in the context of industry 4.0: A structured classification of critical assets and business impacts. Computers in industry, 114, 103165.
Kurakin, A., Goodfellow, I. J., & Bengio, S. (2018). Adversarial examples in the physical world. In Artificial intelligence safety and security (pp. 99-112). Chapman and Hall/CRC.
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 About the Project