A Consent-Based Privacy-Compliant Personal Data-Sharing System

Abstract

Personal data is becoming increasingly valuable in business, as the insights that can be obtained from data processing continue to improve. However, it also can cause adverse effects on individuals. To improve data quality while satisfying privacy compliance, companies now have focused on collecting informed consent from individuals to directly handle personal data without applying any privacy-preserving techniques. Even though the companies obtain consent to use personal data, to improve transparency and accountability to ensure that companies deal with personal data according to consent, it is necessary for a system to comply with privacy requirements. Therefore, this paper proposes a new consent-based privacy-compliant personal data-sharing system that considers personal data-sharing flows and requirements obtained from enterprises and privacy frameworks, respectively. By analyzing a general process and the roles of actors for data sharing in enterprise environments according to standard privacy frameworks, this paper has proposed system requirements, system architecture, and detailed procedure for a consent-based privacycompliant processing method that considers compliance checking as well as consent checking. To show the feasibility of the proposed system, this paper demonstrates a prototype and the performance analysis in the lab and real-world environments.

A Profit Maximization Model for Data Consumers with Data Providers’ Incentives in Personal Data Trading Market

“…Consequently, the personal data provider becomes an important stakeholder in the personal data ecosystem. Therefore, to support and manage explicit consent for data sharing, the concept of a consent management system has been studied [13,14] that can support personal data trading with explicit consent.…”