PETRAS National Centre of Excellence for IoT Systems Cybersecurity is a consortium of eleven leading UK universities which will work together over the next three years to explore critical issues in privacy, ethics, trust, reliability, acceptability, and security.
Knowledge Driven Privacy by Design for IoT
Augmenting Software Design Processes by Developing Knowledge-based AI Technique Towards Assisted Privacy-aware Internet of Things Application Designing
Internet of Things (IoT) applications development and design process is more complicated than others, such as desktop, web, or mobile. That’s because IoT applications need both software and hardware to cooperate across multiple nodes with different capabilities. Moreover, it requires different software engineers with different expertise to cooperate (e.g., frontend, backend, database). Due to the above complications, non-functional requirements, such as privacy tend to be overlooked.
Yearly, a significant number of devices and applications are connecting to the Internet, which raises potential privacy risks. Typically, IoT applications collect and analyse personal data that can be used to derive sensitive information about individuals. However, thus far, privacy concerns have not been explicitly considered (i.e., as unified manner), despite isolated solutions (i.e., a specific technique that address specific privacy challenge) in software engineering processes when designing and developing IoT applications, partly due to a lack of Privacy-by-Design (PbD) methods for the IoT. This project’s primary objective is to develop a Knowledge-based AI technique that assists software engineers by automatically incorporating Privacy by Design (PbD) techniques into a given IoT application design. This project is composed of three main objectives:
- Review and synthesise privacy by design schemes through curating and systematically analysing existing privacy strategies, guidelines, principles, and patterns in the context of IoT.
- Semantically model privacy patterns and IoT systems using knowledge-based AI techniques towards the automated assignment.
- Develop and Evaluate the efficiency and effectiveness of PRIVACY CAPTAIN (Context-Aware Privacy Assistant for the Internet of Things) as a tool for augmenting software engineers’ capabilities and enhancing privacy knowledge.
Team
Partners
PETRAS 2
Outcomes
Poster
Lamya Alkhariji, Suparna De, Omer Rana, and Charith Perera, Ontology Enabled Chatbot for Applying Privacy by Design in IoT Systems, In Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security (CCS '22). Association for Computing Machinery, New York, NY, USA, 3323–3325
Journal
Lamya Alkhariji, Suparna De, Omer Rana, Charith Perera, Semantics-based Privacy by Design for Internet of Things Applications, Future Generation Computer Systems (FGCS), Volume 138, January 2023
Journal
Lamya Alkhariji, Nada Alhirabi, Mahmoud Barhamgi, Mansour Naser Alraja, Omer Rana, Charith Perera, Synthesising Privacy by Design Knowledge Towards Explainable Internet of Things Application Designing in Healthcare, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 17, Issue 2s (62), June 2021 (29)
Journal
Charith Perera, Mahmoud Barhamgi, and Massimo Vecchio, Envisioning Tool Support for Designing Privacy-Aware Internet of Thing Applications, IEEE Internet of Things Magazine (IOTM), Volume 4, Issue 1, March 2021 (6)