深度学习与工业互联网安全:应用与挑战  

Deep Learning and Industrial Internet Security:Application and Challenges

作　　者：杨晨[1] 马瑞成 王雨石 翟岩龙[1] 祝烈煌[1] Yang Chen;Ma Ruicheng;Wang Yushi;Zhai Yanlong;Zhu Liehuang(School of Cyberspace Science and Technology,Beijing Institute of Technology,Beijing 100081,China)

机构地区：[1]北京理工大学网络空间安全学院,北京100081

出　　处：《中国工程科学》2021年第2期95-103,共9页Strategic Study of CAE

基　　金：中国工程院咨询项目“新一代工业互联网安全技术发展战略研究”(2020-XZ-02)。

摘　　要：工业互联网安全是制造强国和网络强国建设的基石,深度学习因其具有表达能力强、适应性好、可移植性高等优点而可支持"智能自主式"工业互联网安全体系与方法构建,因此促进深度学习与工业互联网安全的融合创新具有鲜明价值。本文从产业宏观、安全技术、深度学习系统等角度全面分析了发展需求,从设备层、控制层、网络层、应用层、数据层的角度剖析了深度学习应用于工业互联网安全的发展现状;阐述了工业互联网深度学习应用在模型训练、模型预测方面的安全挑战,前瞻研判了未来研究的重点方向,如深度神经网络可解释性、样本收集和计算成本、样本集不均衡、模型结果可靠性、可用性与安全性平衡等。研究建议,在总体安全策略方面,深化促进两者的融合发展,建立动态的纵深防御体系;在技术攻关研究方面,采用应用驱动和前沿探索相结合的攻关方式,加快领域关键技术问题的攻关突破;在政策支持与引导方面,合理增加交叉领域的资源投入,建立"产学研"联合研发与应用的生态体系。Industrial Internet security is crucial for strengthening the manufacturing and network sectors of China.Deep learning,owing to its strong expression ability,good adaptability,and high portability,can support the establishment of an intelligent and autonomous industrial Internet security system and method.Therefore,it is of great value to promote the integrated innovation of deep learning and industrial Internet security.In this study,we analyze the development demand for industrial Internet security from the perspective of macro industrial environment,security technology,and deep learning system,and summarize the application status of deep learning to industrial Internet security in terms of device,control,network,application,and data layers.The security challenges faced by deep learning application to industrial Internet primarily lie in model training and prediction.Furthermore,we identify key research directions including interpretability of deep neural networks,cost control of sample collection and calculation,imbalance of sample sets,reliability of model results,and tradeoff between availability and security.Finally,some suggestions are proposed:a dynamic defense system in depth should be established in terms of overall security strategy;an application-driven and frontier exploration integrated method should be adopted to achieve breakthroughs regarding key technologies;and resources input should be raised for such interdisciplinary fields to establish an industry–university–research institute joint research ecosystem.

关 键 词：工业互联网安全 物联网安全 深度学习 数据安全 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]