Title: Agreement window algorithm for user controlled and utility supported personal data privacy

Authors: Geocey Shejy; Pallavi Vijay Chavan

Addresses: Department of Computer Engineering, Ramrao Adik Institute of Technology, D.Y. Patil (Deemed to be University), Nerul, Navi Mumbai, Maharashtra, India ' Department of Computer Engineering, Ramrao Adik Institute of Technology, D.Y. Patil (Deemed to be University), Nerul, Navi Mumbai, Maharashtra, India

Abstract: A good privacy-preserving algorithm must keep the trade-off between privacy preservation and the utility of the data for analysis purposes. For fine-tuned protection of individual data privacy, both customers and organisations who are the stakeholders of digital services need more supporting research to ensure legal compliance. The work in this article keeps the European Union's GDPR as a key reference. The agreement window (AW) algorithm ensures ϵ-differential privacy and helps organisations collect legitimate personal data by ensuring user consent. The agreement window is a conceptual space where the data owner and the service-providing organisations agree to share the data. While sharing data in this space, the AW algorithm calculates the sensitivity factor (SF), which is the combined quantity of sensitivity of collecting data by the service provider and is used to decide the noise addition required to be added to the original data.

Keywords: agreement window; differential privacy; set sensitivity; sensitivity factor; personal identifiable information; PII; personal sensitive information; PSI; quasi identifier; QI.

DOI: 10.1504/IJCSE.2025.146073

International Journal of Computational Science and Engineering, 2025 Vol.28 No.3, pp.346 - 357

Received: 14 Jan 2024
Accepted: 31 May 2024
Published online: 06 May 2025 *

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