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A novel privacy paradigm for improving serial data privacy
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Shaukat, Ayesha, Anjum, Adeel, Malik, Saif U. R., Shah, Munam Ali and Maple, Carsten (2022) A novel privacy paradigm for improving serial data privacy. Sensors, 22 (7). e2811. doi:10.3390/s22072811
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Official URL: https://doi.org/10.3390/s22072811
Abstract
Protecting the privacy of individuals is of utmost concern in today’s society, as inscribed and governed by the prevailing privacy laws, such as GDPR. In serial data, bits of data are continuously released, but their combined effect may result in a privacy breach in the whole serial publication. Protecting serial data is crucial for preserving them from adversaries. Previous approaches provide privacy for relational data and serial data, but many loopholes exist when dealing with multiple sensitive values. We address these problems by introducing a novel privacy approach that limits the risk of privacy disclosure in republication and gives better privacy with much lower perturbation rates. Existing techniques provide a strong privacy guarantee against attacks on data privacy; however, in serial publication, the chances of attack still exist due to the continuous addition and deletion of data. In serial data, proper countermeasures for tackling attacks such as correlation attacks have not been taken, due to which serial publication is still at risk. Moreover, protecting privacy is a significant task due to the critical absence of sensitive values while dealing with multiple sensitive values. Due to this critical absence, signatures change in every release, which is a reason for attacks. In this paper, we introduce a novel approach in order to counter the composition attack and the transitive composition attack and we prove that the proposed approach is better than the existing state-of-the-art techniques. Our paper establishes the result with a systematic examination of the republication dilemma. Finally, we evaluate our work using benchmark datasets, and the results show the efficacy of the proposed technique.
| Item Type: | Journal Article | ||||||||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||||||||
| SWORD Depositor: | Library Publications Router | ||||||||||||
| Library of Congress Subject Headings (LCSH): | Data protection, Data privacy, Serial communications | ||||||||||||
| Journal or Publication Title: | Sensors | ||||||||||||
| Publisher: | MDPI | ||||||||||||
| ISSN: | 1424-8220 | ||||||||||||
| Official Date: | 6 April 2022 | ||||||||||||
| Dates: |
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| Volume: | 22 | ||||||||||||
| Number: | 7 | ||||||||||||
| Article Number: | e2811 | ||||||||||||
| DOI: | 10.3390/s22072811 | ||||||||||||
| Status: | Peer Reviewed | ||||||||||||
| Publication Status: | Published | ||||||||||||
| Reuse Statement (publisher, data, author rights): | / | ||||||||||||
| Access rights to Published version: | Open Access | ||||||||||||
| RIOXX Funder/Project Grant: |
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