基于b区块链的电力调度系统联邦异常检测方法

J. Han, Dongdong Huo, Wenqian Zhang, Yazhe Wang
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引用次数: 0

摘要

随着网络技术的进步,电网调度系统日益受到来自互联网的攻击。由于法律和地方管理要求的限制和规定,这些系统很难形成一个共同的力量来检测安全状态,同时保证每个系统数据的隐私性。针对这一问题,本文提出了一种基于区块链的电力调度系统联邦异常检测方法。该方法提供了一种基于树型的联邦隐私训练方案,对来自各个电力调度系统的数据进行聚合,并在不泄露这些数据明文的基础上生成检测精度更高的模型。此外,区块链用于连接跨区域的调度系统,以实现这些系统之间的数据安全传输。实验结果表明,该方法不仅提高了检测攻击的准确性,而且保证了pdp之间数据的保密性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Blockchain based Federal Abnormal Detection Method for Power Dispatching Systems
With the improvement of the network technology, power dispatching systems (PDS) are increasingly attacked from the Internet. Due to the limitations and regulations in laws and local management requirements, it is difficult for such systems to form a joint force to detect the security status while ensuring the privacy of each system's data. Aiming at this issue, this paper proposes a blockchain based federal abnormal detection method for power dispatching systems. The method provides a tree based federal-privacy-training scheme to aggregate data from various power scheduling systems, and generates a model with higher detection accuracy on the basis of not leaking the plaintext of these data. Moreover, the blockchain is used to connect dispatching systems across areas to enable the secure transfer of data between these systems. The experimental results show that this method not only improves the accuracy for detecting attacks, but also ensures the privacy of the data among PDSs.
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