A Survey on Understanding and Representing Privacy Requirements in the Internet-of-Things
Authors: Gideon Ogunniye, Nadin Kokciyan
JAIR 2023 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this survey paper, we review the privacy requirements represented in existing Io T ontologies. We discuss how to extend these ontologies with new requirements to better capture privacy, and we introduce case studies to demonstrate the applicability of the novel requirements. Our methodology is: i) we do a systematic search to identify research papers (surveys and literature reviews) that focus on modelling privacy requirements, ii) we select the research papers that fulfill our predefined selection criteria, and iii) we analyze and present the included research papers in a systematic way and discuss our findings. |
| Researcher Affiliation | Academia | Gideon Ogunniye EMAIL Department of Science, Technology, Engineering and Public Policy (UCL STEa PP), University College London, London, WC1E 6JA, UK; Nadin K okciyan EMAIL School of Informatics, University of Edinburgh, Edinburgh, EH8 9AB, UK |
| Pseudocode | No | The paper provides a conceptual survey and proposes new privacy requirements and a taxonomy. It does not include any structured pseudocode or algorithm blocks for a specific method or procedure. |
| Open Source Code | No | The paper does not provide concrete access to source code. It mentions future work: "Our next steps include the development of a new ontology to capture the social requirements identified in this survey. We will implement a conversational agent model (i.e., a privacy assistant) that uses ontologies to reason about data to make sharing decisions while incorporating the privacy preferences of the users and their feedback." |
| Open Datasets | No | This is a survey paper that reviews existing IoT ontologies and proposes new privacy requirements. It does not conduct empirical experiments that would use or make available a specific dataset for its own methodology. |
| Dataset Splits | No | This paper is a survey and does not involve running experiments on a dataset; therefore, it does not provide dataset split information. |
| Hardware Specification | No | This paper is a survey and does not involve running experiments; therefore, it does not specify any hardware details. |
| Software Dependencies | No | This paper is a survey and does not describe any specific experimental implementations or software tools with version numbers for its own methodology. |
| Experiment Setup | No | This paper is a survey and does not involve running experiments or training models; therefore, it does not provide details on experimental setup or hyperparameters. |