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《中国工程科学》 >> 2021年 第23卷 第2期 doi: 10.15302/J-SSCAE-2021.02.013

深度学习与工业互联网安全:应用与挑战

北京理工大学网络空间安全学院,北京 100081

资助项目 :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) 收稿日期: 2021-01-20 修回日期: 2021-03-06 发布日期: 2021-03-19

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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。

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