Privacy Preserved Consortium Blockchain-Based Decentralized Stock Exchange Platform

The global implementation architecture of the traditional stock market distributes responsibilities and data across different intermediaries, including financial and governmental organizations. Each organization manages its system and collaborates with the others to facilitate trading on the stock exchange platform, and typically buy-sell orders go through different parties before settlement. This design architecture that involves a complex chain of intermediaries has several limitations and shortcomings, such as a single point of failure, a longer time for financial settlements, and weak transparency.In this research, we present a novel blockchain-based architecture for a fully decentralized stock market with a privacy persevering framework which ensures anonymity and unlinkability of the investors’ accounts and their respective trading activities. Our architecture is based on a private Ethereum blockchain to create a consortium network leveraging organizations that are already involved in the traditional stock exchange to act as validating nodes. In our architecture, the stock exchange trading logic is completely implemented on a smart contract, while considering the existing governmental market regulations. We present a proof of concept implementation of the new architecture and measure the buy-sell orders throughput and latency under different network sizes and trading workload scenarios. The obtained results have shown that the proposed trading platform can reach a throughput equivalent to 89% of the optimal throughput when the sending rate is 350 tx/sec. For the proposed framework to meet the privacy requirements of the stock exchange, both the unique account identifier (NIN) that resembles the investor identity and the associated balance information are anonymized through customized data generalization and distortion techniques. The anonymization makes trading transactions unlinkable to their original investors by ensuring that both the NIN and balance are k-anonymous; i.e., k accounts belonging to different investors have the same balance. Moreover, to ensure long-term unlinkability, the process of anonymization is repeated at regular time intervals (every trading session). In addition to anonymity and unlinkability characteristics, the proposed framework is augmented with traceability and non-repudiation features. To assess the effect of the additional privacy procedures on the trading execution time, we conduct several simulations on several market sizes and types. We compare the transaction execution time of our proposed platform against a traditional non-privacy preserving blockchain-based stock exchange. The obtained results show an acceptable execution time overhead.