Smart City Gnosys

Smart city article details

Title Privacy-Preserving Hierarchical Anonymization Framework Over Encrypted Data
ID_Doc 43184
Authors Jia J.; Saito K.; Nishi H.
Year 2024
Published IEEJ Transactions on Electronics, Information and Systems, 144, 10
DOI http://dx.doi.org/10.1541/ieejeiss.144.1011
Abstract Smart cities, which can monitor the real world and provide smart services in a variety of fields, have improved people’s living standards as urbanization has accelerated. However, there are security and privacy concerns because smart city applications collect large amounts of privacy-sensitive information from people and their social circles. Anonymization, which generalizes data and reduces data uniqueness, is an important step in preserving the privacy of sensitive information. However, anonymization methods frequently require large datasets and rely on untrusted third parties to collect and manage data, particularly in a cloud environment. In this case, private data leakage remains a critical issue, discouraging users from sharing their data and impeding the advancement of smart city services. This problem can be solved if the computational entity performs anonymization without obtaining the original plain text. This study proposed a hierarchical k-anonymization framework using homomorphic encryption and secret sharing composed of two types of domains. Different computing methods are selected flexibly, and two domains are connected hierarchically to obtain higher-level anonymization results efficiently. The experimental results show that connecting two domains can accelerate the anonymization process, indicating that the proposed secure hierarchical architecture is practical and efficient. © 2024 The Institute of Electrical Engineers of Japan.
Author Keywords homomorphic encryption; k-anonymization; secret sharing


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