论文标题
AI在行业应用中的安全和安全方面
Security and Safety Aspects of AI in Industry Applications
论文作者
论文摘要
在这个相对非正式的讨论纸中，我们总结了机器学习安全和保障领域的问题，这些问题将在未来五到十年内影响行业领域。近年来，使用神经网络分类的各种产品，通常在与视觉相关的应用中，但也是预测性维护中的各种产品。尽管如此，关于安全和安全与安全领域的潜在问题的报告，例如对抗性攻击，使早期采用者尚未解决，并威胁要阻碍更广泛的规模采用这项技术。现实世界中适用性的问题在于能够评估应用这些技术的风险。在本讨论纸中，我们描述了到达机器学习神经网络分类器的过程，该过程指出了该工作流程中的安全性和安全性漏洞，并以相关的研究为特定。
In this relatively informal discussion-paper we summarise issues in the domains of safety and security in machine learning that will affect industry sectors in the next five to ten years. Various products using neural network classification, most often in vision related applications but also in predictive maintenance, have been researched and applied in real-world applications in recent years. Nevertheless, reports of underlying problems in both safety and security related domains, for instance adversarial attacks have unsettled early adopters and are threatening to hinder wider scale adoption of this technology. The problem for real-world applicability lies in being able to assess the risk of applying these technologies. In this discussion-paper we describe the process of arriving at a machine-learnt neural network classifier pointing out safety and security vulnerabilities in that workflow, citing relevant research where appropriate.
