A Privacy Preserving Blockchain Based Framework for AIoT Data Exchange

• Main Authors: Chou, Shih-Fan, Kuo, Yi-Lin, Shih, Yuan-Yao
• Format: Conference Proceeding
• Language: English
• Subjects: AIoT; Blockchain; Blockchains; Data Exchange; Data privacy; Error analysis; Internet of Things; IPFS; Privacy; Privacy Preserving; Proposals; Wireless communication
• ISSN: 1558-2612
• DOI: 10.1109/WCNC51071.2022.9771669

Thanks to the advances in wireless communication technologies and the popularity of mobile devices, individuals can now record and produce personal videos. Furthermore, with the power of machine learning techniques, one can envision that a new paradigm for AIoT, a combination of AI and IoT, can accomplish many novel IoT applications. A feasible, safe, and trusty data trading environment is necessary to realize this AIoT service paradigm. The classic approach of centralized trust centers is not suitable for the targeted scenario due to privacy, vulnerability, and efficiency concerns. The emerging blockchain technology could be the perfect solution; yet, it remains a challenging issue to ensure data provider's privacy. Thus, this paper envisions a blockchain- based AIoT service paradigm and proposes solutions for preserving privacy. To preserve privacy in data storage, we adopt the approach of a private InterPlanetary File System (IPFS) network. For preserving privacy in on-chain metadata, especially the GPS records of the personal videos, we propose a privacy-preserving geometric search scheme (PPGSS). Through extensive experiments using real- world datasets and settings, we demonstrate the effectiveness of the proposed scheme.