# A Blockchain-Based Privacy-Preserving and Fair Data Transaction Model in IoT
## 1 Introduction  
With the widespread development and application of Internet of Things (IoT) technology, vast amounts of data from IoT sensors are collected, stored, and utilized [1]. Data from a single sensor often fails to meet the requirements of users. The true value of IoT lies in the sharing and comprehensive use of diverse sensing data. Data sharing promotes the distribution of data resources, elevating work efficiency and quality, while spurring innovative applications. For instance, in healthcare, data sharing can provide valuable records of patient treatments and physical examinations, assisting medical professionals in providing more targeted treatment plans [2]. In data markets, novel data transaction models have emerged that allow data owners to sell their information to consumers. Big data has evolved into a valuable asset [3]. However, the current IoT system architecture is based on client-server communication. IoT devices are connected to a central cloud server which is used to ensure the communication between devices and handle and store data. This centralized architecture may create a single point of failure. This may increase security and privacy risks. Therefore, it is necessary to adopt a new solution based on decentralized architecture [4]. Additionally, during data transactions, due to the inherent mistrust between data providers and consumers, the latter might delay or refuse payments after obtaining the data. Similarly, providers could withhold datasets after receiving compensation, making fair payments between parties hard to ensure. Given the aforementioned challenges in security, privacy preservation, and fair payment, many data owners are reluctant to provide their data to third-party trading platforms. The big data industry grapples with the challenge of \"data islands\". Hence, there is an imperative need to adopt a decentralized data-sharing framework and establish a secure, efficient data transaction model that ensures fair payment and safeguards data providers' privacy during transactions. Blockchain, as a distributed ledger, embodies characteristics of decentralization, immutability, and auditability and is frequently employed to address security issues tied to traditional IoT systems [5]. Compared to conventional centralized IoT systems, a decentralized IoT system based on blockchain has several advantages: firstly, it achieves end-to-end communication without involving centralized servers, reducing single-point failure risks and bolstering fault tolerance; secondly, nodes on the blockchain can verify the integrity and identity information of data uploaded by other nodes, which can prevent malicious data tampering and ensure the security and consistency of the blockchain network; finally, blockchains store data and event logs in an immutable manner, giving blockchain-based IoT systems traceability and accountability. Nevertheless, each node in the blockchain maintains a local backup of the entire blockchain to uphold the network's integrity. Given that all nodes have access to blockchain data, this backup mechanism has raised growing concerns about privacy. There's a potential risk of sensitive information being exposed. Traditional privacy-preserving techniques, such as anonymization and generalization, have proven inadequate when faced with attackers possessing background knowledge [6]. This inadequacy is evident from significant privacy leaks in datasets like AOL [7] and Netflix [8], leading to questions about the effectiveness of these methods in protecting user privacy. Differential privacy, which is a notable method to counter attackers with background knowledge, operates by adding random \"noise\" to datasets to ensure data privacy [9; 10]. However, while differential privacy introduces \"noise\" to maintain privacy, it compromises data availability. Determining the right amount of \"noise\" to strike a balance between dataset availability and privacy remains a research challenge.