A Valid Blockchain-based Data Trading Ecosystem

Data, an important asset in digital economy, has fueled the emergence of a new data trading market. Big data market can efficiently promote data trading and further increases the utility of data. However, to realize effective data trading, several challenges needs to be resolved. First, it needs to resolve disputes over data availability in the data trading. Second, atomic exchange and payment fairness between the seller and the buyer are hard to guarantee. Third, data trading platform is the single-point-failure. In this paper, we resolve these challenges by presenting a valid blockchain-based data trading ecosystem. The ecosystem constructs a decentralized arbitration mechanism to address the dispute over data availability in data trading. The ecosystem also designs a sale contract and a deterministic public-key encryption algorithm to guarantee fairness of data trading between the seller and buyer. The features of blockchain is preventing single-point-failure of data trading platform. We prove the desirable security properties that a secure data trading ecosystem should have. Discussion of the presented ecosystem is given. To demonstrate availability, we implement our proposed data trading ecosystem using smart contract in Solidity and program in Java, and evaluate its performance.

[1]  Xinyu Yang,et al.  On binary decomposition based privacy-preserving aggregation schemes in real-time monitoring systems , 2015, 2015 IEEE International Conference on Communications (ICC).

[2]  Jinchuan Chen,et al.  Bootstrapping a Blockchain Based Ecosystem for Big Data Exchange , 2017, 2017 IEEE International Congress on Big Data (BigData Congress).

[3]  Xinwen Fu,et al.  A Survey on Big Data Market: Pricing, Trading and Protection , 2018, IEEE Access.

[4]  Gil Segev,et al.  Deterministic Public-Key Encryption for Adaptively Chosen Plaintext Distributions , 2013, EUROCRYPT.

[5]  Wei Yu,et al.  Smart city: The state of the art, datasets, and evaluation platforms , 2017, 2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS).

[6]  Leonid Reyzin,et al.  A Unified Approach to Deterministic Encryption: New Constructions and a Connection to Computational Entropy , 2012, TCC.

[7]  Xinyu Yang,et al.  A Survey on Internet of Things: Architecture, Enabling Technologies, Security and Privacy, and Applications , 2017, IEEE Internet of Things Journal.

[8]  Xiaojiang Du,et al.  Machine learning based privacy-preserving fair data trading in big data market , 2019, Inf. Sci..

[9]  Hoeteck Wee,et al.  Dual Projective Hashing and Its Applications - Lossy Trapdoor Functions and More , 2012, EUROCRYPT.

[10]  Aggelos Kiayias,et al.  Ouroboros: A Provably Secure Proof-of-Stake Blockchain Protocol , 2017, CRYPTO.

[11]  Jiayu Zhou,et al.  Distributed Data Vending on Blockchain , 2018, 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData).

[12]  Adam O'Neill,et al.  Deterministic Encryption: Definitional Equivalences and Constructions without Random Oracles , 2008, CRYPTO.

[13]  Serge Fehr,et al.  On Notions of Security for Deterministic Encryption, and Efficient Constructions without Random Oracles , 2008, CRYPTO.

[14]  Xue-wen Chen,et al.  Big Data Deep Learning: Challenges and Perspectives , 2014, IEEE Access.

[15]  Silvio Micali,et al.  Probabilistic Encryption , 1984, J. Comput. Syst. Sci..

[16]  Siani Pearson,et al.  Accountability for Data Governance in Cloud Ecosystems , 2013, 2013 IEEE 5th International Conference on Cloud Computing Technology and Science.

[17]  Zvika Brakerski,et al.  Better Security for Deterministic Public-Key Encryption: The Auxiliary-Input Setting , 2011, Journal of Cryptology.

[18]  Tanja Lange,et al.  High-speed high-security signatures , 2011, Journal of Cryptographic Engineering.

[19]  Mohsen Guizani,et al.  Deep Learning for IoT Big Data and Streaming Analytics: A Survey , 2017, IEEE Communications Surveys & Tutorials.

[20]  Omer Reingold,et al.  Incremental Deterministic Public-Key Encryption , 2012, EUROCRYPT.

[21]  Mihir Bellare,et al.  Deterministic and Efficiently Searchable Encryption , 2007, CRYPTO.

[22]  John A. Stankovic,et al.  Research Directions for the Internet of Things , 2014, IEEE Internet of Things Journal.

[23]  Andrea Zanella,et al.  Internet of Things for Smart Cities , 2014, IEEE Internet of Things Journal.

[24]  Yun Ling,et al.  Fine-Grained Two-Factor Protection Mechanism for Data Sharing in Cloud Storage , 2018, IEEE Transactions on Information Forensics and Security.

[25]  Wei Xiong,et al.  Smart Contract Based Data Trading Mode Using Blockchain and Machine Learning , 2019, IEEE Access.

[26]  Thomas Pornin.  Deterministic Usage of the Digital Signature Algorithm (DSA) and Elliptic Curve Digital Signature Algorithm (ECDSA) , 2013, RFC.

[27]  Wei Zhao,et al.  Design and Realization of WInternet , 2016, ACM Trans. Cyber Phys. Syst..

[28]  Kim-Kwang Raymond Choo,et al.  SDTE: A Secure Blockchain-Based Data Trading Ecosystem , 2020, IEEE Transactions on Information Forensics and Security.

[29]  Nick Szabo,et al.  Formalizing and Securing Relationships on Public Networks , 1997, First Monday.

[30]  Joseph K. Liu,et al.  Privacy-Preserving Ciphertext Multi-Sharing Control for Big Data Storage , 2015, IEEE Transactions on Information Forensics and Security.

[31]  Hovav Shacham,et al.  Hedged Public-Key Encryption: How to Protect against Bad Randomness , 2009, ASIACRYPT.

[32]  Xiang-Yang Li,et al.  AccountTrade: Accountable protocols for big data trading against dishonest consumers , 2017, IEEE INFOCOM 2017 - IEEE Conference on Computer Communications.

[33]  Erik Brynjolfsson,et al.  Big data: the management revolution. , 2012, Harvard business review.

[34]  J. Manyika.  Big data: The next frontier for innovation, competition, and productivity , 2011 .

[35]  Houbing Song,et al.  Internet of Things and Big Data Analytics for Smart and Connected Communities , 2016, IEEE Access.

[36]  Guillermo Navarro-Arribas,et al.  A Fair Protocol for Data Trading Based on Bitcoin Transactions , 2017, IACR Cryptol. ePrint Arch..