A Searchable Re-encryption-based Scheme for Massive Data Transactions
Yang Yu, Rui Jin, Hao Yin, Keke Gai, Zijian Zhang · 2022
In the era of big data, companies require to analyze user behaviors and customize personalized services through massive amounts of data. Coupled with the rapid development of data-centric deep learning algorithms, the demand for data transactions has also increased. Current data owners can entrust cloud storage to overcome the limitations of storage capacity and network performance, but such a data transaction model still has two key issues that need to be resolved. On the one hand, when consumers retrieve the encrypted data that are stored in cloud storage, cloud storage may tamper with the returned results. On the other hand, when there is no trusted third party, it is difficult to restrict malicious transactions and ensure the fairness of both parties to the transaction. In this article, we propose a searchable re-encryption scheme for data transactions to prevent cloud storage from returning incorrect results. We also designed a smart contract to limit malicious behaviors in the transaction process to ensure fair transactions. Security analysis and evaluation experiments show that the system takes into account both security and performance, and is more feasible and practical for massive data transaction scenarios.