网络物理制造系统中在线流传感器数据保护的区块链支持方法

Zhangyue Shi, Chenang Liu, Chen Kan, Wenmeng Tian, Yang Chen
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引用次数: 2

摘要

随着物联网和信息技术的快速发展,越来越多的制造系统实现了网络化,极大地提高了制造的灵活性和生产率。此外,各种在线传感器也通常被纳入制造系统中,用于在线质量监测和控制。然而,网络环境也可能使收集到的在线流传感器数据面临网络物理攻击的高风险。具体来说,网络物理攻击可能发生在制造过程中,恶意篡改传感器数据,这可能导致假警报或异常检测失败。此外,网络物理攻击还可能在未经授权的情况下非法访问收集到的数据,造成关键信息的泄露。因此,开发一种有效的方法来保护在线流数据免受这些攻击,从而确保制造系统的网络物理安全变得至关重要。为了实现这一目标,通过利用不对称加密和伪装技术,提出了一种集成的区块链支持方法。提供了一个真实的案例研究,保护增材制造中收集的流数据的网络物理安全,以证明所提出方法的有效性。结果表明,该方法可以在较短的时间内检测到恶意篡改,大大降低了未经授权访问数据的风险。
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A Blockchain-Enabled Approach for Online Stream Sensor Data Protection in Cyber-Physical Manufacturing Systems
With the rapid development of the Internet of Things and information technologies, more and more manufacturing systems become cyber-enabled, which significantly improves the flexibility and productivity of manufacturing. Furthermore, a large variety of online sensors are also commonly incorporated in the manufacturing systems for online quality monitoring and control. However, the cyber-enabled environment may pose the collected online stream sensor data under high risks of cyber-physical attacks as well. Specifically, cyber-physical attacks could occur during the manufacturing process to maliciously tamper the sensor data, which could result in false alarms or failures of anomaly detection. In addition, the cyber-physical attacks may also illegally access the collected data without authorization and cause leakage of key information. Therefore, it becomes critical to develop an effective approach to protect online stream data from these attacks so that the cyber-physical security of the manufacturing systems could be assured. To achieve this goal, an integrative blockchain-enabled method, is proposed by leveraging both asymmetry encryption and camouflage techniques. A real-world case study that protects cyber-physical security of collected stream data in additive manufacturing is provided to demonstrate the effectiveness of the proposed method. The results demonstrate that malicious tampering could be detected in a relatively short time and the risk of unauthorized data access is significantly reduced as well.
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