基于区块链的食品安全知识图谱可信管理探究

doi:10.19788/j.issn.2096-6369.230311

Abstract

Abstract:

In recent years, knowledge graphs have played an important role in the field of food safety. However, there are several issues with food safety knowledge graph information in the whole-life cycle circulation, such as severe data centralization, poor information circulation, easy data tampering, low traceability efficiency, and sharing and co-management difficulty. As an innovative architecture of the new generation of information technology, blockchain offers a new solution for the circulation and management of food safety knowledge graph with its features of decentralization, distributed processing, high privacy, open and transparent data, and difficult data tampering. This paper first analyzes the current situation and critical problems of food safety knowledge graph. Then, it reviews the application status of blockchain in the field of food safety. Based on this, a trustworthy management framework for food safety knowledge graph based on blockchain is constructed. Meanwhile, it designs a multimodal storage mode suitable for food safety knowledge graph, R-TBFT consensus optimization mechanism combined with Raft and TBFT consensus mechanism, and customized smart contracts for food safety knowledge graph. Finally, through the analysis of the feasibility and operation process of the proposed model, it is shown that this model can realize the sharing and interoperability of food safety knowledge graph along the entire chain. It can also ensure the security and reliability of data storage and transmission, providing a reliable source of food information for enterprises, regulatory authorities, and consumers. In summary, this paper provides a feasible solution and valuable reference for the innovative application of new generation information science in the field of food safety.

Key words: knowledge graph, food safety, blockchain, trusted management, smart contract

LIU YuJie, LIAN XiaoQin, ZHAO ZhiYao, LI Yue, ZHANG Xin. Research on Trusted Management of Blockchain-based Food Safety Knowledge Graph[J].Journal of Agricultural Big Data, 2023, 5(3): 69-82.

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References 46

[1]	范丽, 丁一, 傅骏青, 等. 食品添加剂的应用及安全性研究[J]. 食品安全导刊, 2022(31): 4-6.
[2]	余学军. 食品供应链管理机制下的食品安全问题处理对策[J]. 食品安全质量检测学报, 2017, 8(01): 308-311.
[3]	赵鹏. 新时代食品安全监管存在的问题及对策[J]. 中国食品工业, 2022, (18): 78-80+98.
[4]	漆桂林, 高桓, 吴天星. 知识图谱研究进展[J]. 情报工程, 2017, 3(1): 4-25.
[5]	Zou X H. A Survey on application of knowledge graph[J]. Phys Conf Ser, 2020, 1487: 012016. doi: 10.1088/1742-6596/1487/1/012016
[6]	李娜. 食品安全应急处置流程知识图谱构建方法研究[D]. 天津: 天津科技大学, 2020.
[7]	赵良, 张赵玥, 廖子逸, 等. 用BERT和改进PCNN模型抽取食品安全领域关系[J]. 农业工程学报, 2022, 38(8): 263-270.
[8]	王尔媚, 苏静. 基于区块链的食品供应链溯源平台[J]. 食品工业, 2022, 43(11): 227-230.
[9]	A. Alammary, S. Alhazmi, M. Almasri, et al. Blockchain-based applications in education: A systematic review[J]. Applied Sciences, 2019, 9(12): 2400. doi: 10.3390/app9122400
[10]	A. Tandon, A. Dhir, A. K. M. N. Islam, et al. Blockchain in healthcare: A systematic literature review synthesizing framework and future research agenda[J]. Computers in Industry, 2020, 122.
[11]	F. Antonucci, S. Figorilli, C. Costa, et al. A review on blockchain applications in the agri-food sector[J]. Journal of the Science of Food and Agriculture, 2019, 99(14): 6129-6138. doi: 10.1002/jsfa.9912 pmid: 31273793
[12]	M. Pournader, Y. Shi, S. Seuring, et al. Blockchain applications in supply chains transport and logistics: A systematic review of the literature[J]. International Journal of Production Research, 2020, 58(7): 2063-2081. doi: 10.1080/00207543.2019.1650976
[13]	董云峰, 张新, 许继平, 等. 基于区块链的粮油食品全供应链可信追溯模型[J]. 食品科学, 2020, 41(9): 30-36. doi: 10.7506/spkx1002-6630-20190418-227
[14]	许继平, 孙鹏程, 张新, 等. 基于区块链的粮油食品全供应链信息安全管理原型系统[J]. 农业机械学报, 2020, 51(2): 341-349.
[15]	周清杰, 代冰琳. 区块链助力食品安全智慧监管[J]. 中国市场监管研究, 2020(10): 70-72.
[16]	Chen Z, Wang Y H, Zhao B, et al. Knowledge graph completion: A review[J]. IEEE Access, 2020, 8:192435-192456. doi: 10.1109/Access.6287639
[17]	周毓奇, 曹蕊. 基于知识图谱的食品问题溯源系统[J]. 信息与电脑(理论版), 2022, 34(6): 171-174+179.
[18]	Hu Z R, Weng C Y, Qin L, et al. Food Inspection Data Analysis System based on Knowledge Graph[C]. 2022 2nd International Conference on Consumer Electronics and Computer Engineering (ICCECE), 2022.
[19]	张朝正, 陈婷, 潘登, 等. 冬奥会食品供应链有害因子知识图谱和智能化快筛技术研究[J]. 中国食品卫生杂志, 2022, 34(5): 884-888.
[20]	乔青青, 郝莉花, 马江涛, 等. 基于知识图谱的炒货食品抽检数据可视化系统研究[J]. 食品工业, 2023, 44(2): 123-126.
[21]	管铮懿, 周淑娟, 雷永琪. 基于Neo4j的食品安全知识图谱构建研究[J]. 信息与电脑(理论版), 2021, 33(6): 45-48.
[22]	吴帅, 雷声, 杨锡洪, 等. 指纹分析技术及其在食品中的应用[J]. 食品与机械, 2015, 31(1): 249-252+268.
[23]	田怀香, 陈彬, 孙学锋, 等. 指纹图谱技术在生鲜乳掺假检测中的研究进展[J]. 食品安全质量检测学报, 2020, 11(17): 5837-5843.
[24]	张玉华, 孟一, 姜沛宏, 等. 气味指纹技术在食品品质安全检测中的应用[J]. 食品工业科技, 2013, 34(18): 362-365.
[25]	李月明, 韩冰, 王军茹, 等. 气味指纹图谱技术在肉类产品中的应用研究进展[J]. 食品与机械, 2022, 38(5): 210-215+225.
[26]	张梦琦. 区块链技术下农产品供应链溯源系统研究[J]. 农村. 农业. 农民(B版), 2022, (5): 20-21.
[27]	阙迪文. 食品安全管理中区块链技术应用的要点分析[J]. 食品安全导刊, 2020(30): 156.
[28]	苏丹, 王志霞, 周佳, 等. 基于区块链技术的普洱茶贮藏安全监管探讨[J]. 食品安全质量检测学报, 2021, 12(16): 6636-6641.
[29]	徐睿, 孙霞, 郭业民, 等. 基于区块链技术的食品安全溯源体系应用与研究进展[J]. 食品安全质量检测学报, 2020, 11(20): 7610-7616.
[30]	刘国翔, 董凯宁. 基于区块链技术的信息安全监管——以食品信息安全监管为例[J]. 中国科技资源导刊, 2019, 51(3): 91-95.
[31]	刘佳琦, 游新冬, 吕学强, 等. 区块链技术在食品溯源行业的研究[J]. 食品工业, 2021, 42(11): 273-277.
[32]	王坤侠. 基于区块链技术的茶叶食品安全追溯体系分析[J]. 福建茶叶, 2022, 44(5): 35-37.
[33]	朱建明, 张沁楠, 高胜. 区块链关键技术及其应用研究进展[J]. 太原理工大学学报, 2020, 51(3): 321-330.
[34]	张新, 彭祥贞, 李悦, 等. 基于可信区块链和可信标识的粮油食品全供应链信息追溯模型[J]. 农业大数据学报, 2022, 4(1): 35-48.
[35]	于坚, 孙嘉笛, 纪剑, 等. 区块链技术在食品溯源体系中的应用[J]. 食品工业科技, 2021, 42(15):377-382.
[36]	宋胜红, 周琴, 胡露, 等. 基于区块链的溯源问题研究[J]. 江苏通信, 2022, 38(3): 54-56.
[37]	李明佳, 汪登, 曾小珊, 等. 基于区块链的食品安全溯源体系设计[J]. 食品科学, 2019, 40(3): 279-285. doi: 10.7506/spkx1002-6630-20171026-299
[38]	A. Shahid, A. Almogren, N. Javaid, et al. Blockchain-Based Agri- Food Supply Chain: A complete solution[J]. IEEE Access, 2020, 8: 69230-69243. doi: 10.1109/Access.6287639
[39]	Li Y, Sun YH, Yang Q, et al. Method of reaching consensus on probability of food safety based on the integration of finite credible data on block chain[J]. IEEE Access, 2021, 9: 123764-123776. doi: 10.1109/ACCESS.2021.3108178
[40]	Tao Q, Cui X H, Huang X F, et al. Food safety supervision system based on Hierarchical Multi-Domain Blockchain Network[J]. IEEE Access, 2019, 7: 51817-51826. doi: 10.1109/ACCESS.2019.2911265
[41]	黄彦斌. 区块链技术在食品安全管理中的应用研究[J]. 食品安全导刊, 2022(18): 48-50.
[42]	余东来. 区块链技术在食品可追溯领域的应用研究[J]. 食品安全导刊, 2022(4): 167-170.
[43]	代闯闯, 栾海晶, 杨雪莹, 等. 区块链技术研究综述[J]. 计算机科学, 2021, 48(S2): 500-508.
[44]	Deng X H, Li K T, Wang Z Q, et al. A Survey of Blockchain Consensus Algorithms[C]. 2022 International Conference on Blockchain Technology and Information Security (ICBCTIS), 2022.
[45]	Li W Y, Feng C L, Zhang L, et al. A Scalable Multi-Layer PBFT Consensus for Blockchain[J]. IEEE Transactions on Parallel and Distributed Systems, 2021, 32(5): 1146-1160. doi: 10.1109/TPDS.2020.3042392
[46]	Zheng Z B, Xie S A, Dai H N. An overview on smart contracts: Challenges, advances and platforms[J]. Future Generation Computer Systems, 2020, 105: 475-491. doi: 10.1016/j.future.2019.12.019

产品条码	食品名称	食品类别	生产日期	生产地	所含添加剂条码
52899600	猪肉	肉禽蛋	2023.3.20	北京顺义	1001
52899601	黄鱼	水制品	2023.3.20	北京顺义	1010

添加剂条码	添加剂名称	添加作用	超标可能造成的人体危害
1001	丙酸钠	防腐剂	腹泻、恶心、呕吐
1010	乳酸钠	抗氧化剂	肠道不适、腹痛

Research on Trusted Management of Blockchain-based Food Safety Knowledge Graph

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