Application of Blockchain and Fully Homomorphic Encryption in Online Questionnaires
DOI:
https://doi.org/10.54097/hset.v39i.6674Keywords:
Blockchain; Fully Homomorphic Encryption; Online Questionnaires.Abstract
An online questionnaire is a simple and efficient method of acquiring diverse data for surveys. However, a proportion of respondents have strong concerns about whether questionnaires in this form will leak their privacy, which causes their unwillingness to fill out the questionnaires. Blockchain is well known for decentralization, traceability, and transparency and is now widely used in all kinds of platforms. Fully homomorphic encryption is another popular technique that ensures the safety of privacy, it helps to compute and use encrypted data without decrypting it. To solve privacy-preservation problems and enhance online data sharing, this paper dedicates to demonstrating how the merits of Blockchain and Fully Homomorphic Encryption (FHE) can be utilized to realize a secure, reliable, and decentralized online-questionnaire platform that guarantees the authenticity of data and privacy security for clients. This paper also proves that the combination of blockchain and FHE can successfully meet the expectation of an ideal online questionnaire platform.
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References
Martyn Denscombe. The length of responses to open-ended questions: A comparison of online and paper questionnaires in terms of a mode effect. Social Science Computer Review, 2008, 26(3): 359-368.
Samúel Lefever, Michael Dal, Ásrún Matthíasdóttir. Online data collection in academic research: advantages and limitations. British Journal of Educational Technology, 2007, 38(4): 574-582.
Paul van Schaik, Su Luan Wong, Timothy Teo. Questionnaire layout and national culture in online psychometrics. International journal of human-computer studies, 2015, 73: 52-65.
Yang Lu. The blockchain: State-of-the-art and research challenges. Journal of Industrial Information Integration, 2019, 15: 80-90.
Kei Leo Brousmiche, Thomas Heno, Christian Poulain, Antoine Dalmieres, Elyes Ben Hamid. Digitizing, securing and sharing vehicles life-cycle over a consortium blockchain: Lessons learned. 2018 9th IFIP international conference on new technologies, mobility and security (NTMS). IEEE, 2018: 1-5.
Gu Jingjing, Sun Binglin, Du Xiaojiang, Wang Jun, et al. Consortium blockchain-based malware detection in mobile devices. IEEE Access, 2018, 6: 12118-12128.
Lin Iuon-Chang, Liao Tzu-Chun. A survey of blockchain security issues and challenges. Int. J. Netw. Secur., 2017, 19(5): 653-659.
Sercan Ozcan, Unalan Serhan. Blockchain as a general-purpose technology: Patentometric evidence of science, technologies, and actors. IEEE Transactions on Engineering Management, 2020.
Li Xiaoqi, Jiang Peng, ChenTing, Luo Xiapu, et al. A survey on the security of blockchain systems. Future Generation Computer Systems, 2020, 107: 841-853.
Bernardo Pulido-Gaytan, Andrei Tchernykh, Jorge M Cortés-Mendoza, et al. Privacy-preserving neural networks with Homomorphic encryption: Challenges and opportunities. Peer-to-Peer Networking and Applications, 2021, 14(3): 1666-1691.
Alexander Wood, Kayvan Najarian, Delaram Kahrobaei. Homomorphic encryption for machine learning in medicine and bioinformatics. ACM Computing Surveys (CSUR), 2020, 53(4): 1-35.
Song Weitao, Hu Bin, Zhao XiuFeng. One Improved RLWE-based FHE and Fast Private Information Retrieval. KSII Transactions on Internet and Information Systems (TIIS), 2019, 13(12): 6260-6276.
Shen Meng, Tang Xiangyun, Zhu Liehuang, Du Xiaojiang, et al. Privacy-preserving support vector machine training over blockchain-based encrypted IoT data in smart cities. IEEE Internet of Things Journal, 2019, 6(5): 7702-7712.
Craig Gentry. A fully homomorphic encryption scheme. Stanford university, 2009.
Pin-Chun Chen, Kuo Tzu-Hsiang, Wu Ja-Ling. A Study of the Applicability of Ideal Lattice-Based Fully Homomorphic Encryption Scheme to Ethereum Blockchain. IEEE Systems Journal, 2021, 15(2): 1528-1539.
Jung Hee Cheon, Hyeongmin Choe, Donghwan Lee, Yongha Son. Faster Linear Transformations in HElib, Revisited. IEEE Access, 2019, 7: 50595-50604.
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