## 1 Introduction
### State of the Art  
In this sub-section, we explore the literature around data trading services using blockchain, which discusses data trading, and sharing data securely, respecting the user's privacy concerns. A Decentralized Review System for Data Marketplaces [5] hosting urban quality of life data, vehicle data and other IoT data is designed to replace the conventional centralized rating systems. The Decentralized Data Marketplace consists of the critical elements wherein the buyers and sellers of data interface through the marketplace for data transfer, buying, querying the data, reviewing the data, and providing ratings to the data. The system allocates pre-determined credible reviewers against a set of products in a randomized and double-blinded method to minimize actor collusion and gaining illegal advantage out of any transaction. Reviewers are incentivized through game theoretical modeling, where they identify the conditions for Nash Equilibrium policy for the reviewers. The Nash Equilibrium policy aims at finding an optimal solution to a problem with competitive participants. The system is presented as a general framework and analyzed theoretically with no decentralized platform implementation. The presented work is simulated using NashPy Library, where as long as sufficient incentives increase the probability of a full review, the review quality is enhanced. But there are still some pertinent questions unanswered in this work: (1) the formation of a review committee when the platform is still new and the absence of reviewer credentials, (2) the strategy to review a product continuously or at a determined time frequency, (3) the issue of preservation of the seller's privacy behind the transaction process and (4) the scalability potential of the system with increasing products, reviewers and sellers. A credible data trading system for IoT data minimizing the risk of fraud and transactions is proposed in [6]. The system permits the data producers and consumers to agree on data and settle the payment on the chain. A credit mechanism is developed to lower the fees incurred during the private Ethereum network implementation participation process. This system's objectives are Consumer Fairness, where customers do not pay for data not received; Producer Fairness, ensuring the minimal risk of data loss; and Privacy, limiting data visibility at a minimal operational cost. The system is evaluated regarding gas consumption and incurred blockchain transactions for the trading scheme, as the idea is to minimize the transaction cost related to transaction gas complexity. Around 35,000 units of gas is estimated for fund deposit transactions and higher for receipt transactions as it needs data signature checking. A consensus-based distributed auction scheme for data sharing is proposed in [7] for privacy preservation and avoiding malicious collusion of actors. The scheme allows for the participants to group into clusters for privacy and then reach a consensus. The mechanism is further incentivized to share data without privacy leakages. Differential privacy, symmetric encryption and zero-knowledge proofs are incorporated to design the auction mechanism for a trade-off between privacy preservation and social efficiency. The consensus algorithm is constructed where different kinds of witnesses are selected using anonymous verifiable random functions. It is performed without peer interactions and different parallel operations by varying witnesses to verify the proof and result, ensuring finalization. The evaluation of the system shows that the participants reach a consensus on the auction result with low computation and communication costs. A novel proposition of data marketplace design that satisfies all desirable properties in any system of fairness, efficiency, security, privacy, and regulation adherence is proposed in [8]. The authors implement FairSwap [9] to guarantee fairness where the participants agree on a value wherein a Proof of Misbehavior is generated to punish in case of wrongdoing.