Semi-asynchronous federated learning-based privacy-preserving intrusion detection for advanced metering infrastructure

IF 4.1 3区 工程技术 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Zhuoqun Xia , Hongmei Zhou , Zhenzhen Hu , Qisheng Jiang , Kaixin Zhou
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引用次数: 0

Abstract

The emergence of smart grid brings great convenience to users and power companies, but also brings many new problems, among which the most prominent one is network attack security. Although federated learning works well in dealing with smart grid network attacks, it suffers from gradient leakage, client node failure and a single type of training model. Therefore, this paper proposes a semi-asynchronous federated learning-based privacy-preserving intrusion detection for advanced metering infrastructure (AMI). First, we design a hierarchical federated learning framework based on chained secure multiparty computing, which allows concentrators to collaboratively train models to protect local gradients. Second, we adapt the framework to the AMI network structure characteristics, and design a semi-asynchronous model distribution protocol. Finally, we build an ensemble model based on temporal convolutional network and gated recurrent unit (TCN-GRU) to detect AMI network attacks. The experimental results show that the proposed method can achieve 99.23% accuracy than existing methods.
基于半异步联邦学习的高级计量基础设施隐私保护入侵检测
智能电网的出现在给用户和电力公司带来极大便利的同时,也带来了许多新的问题,其中最突出的是网络攻击安全问题。尽管联邦学习在处理智能电网网络攻击方面效果良好,但它存在梯度泄漏、客户端节点故障和单一类型的训练模型等问题。为此,本文提出了一种基于半异步联邦学习的高级计量基础设施(AMI)隐私保护入侵检测方法。首先,我们设计了一个基于链式安全多方计算的分层联邦学习框架,该框架允许集中器协同训练模型以保护局部梯度。其次,根据AMI网络的结构特点,设计了半异步模型分布协议。最后,我们建立了一个基于时间卷积网络和门控循环单元(TCN-GRU)的集成模型来检测AMI网络攻击。实验结果表明,该方法与现有方法相比,准确率达到99.23%。
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来源期刊
International Journal of Critical Infrastructure Protection
International Journal of Critical Infrastructure Protection COMPUTER SCIENCE, INFORMATION SYSTEMS-ENGINEERING, MULTIDISCIPLINARY
CiteScore
8.90
自引率
5.60%
发文量
46
审稿时长
>12 weeks
期刊介绍: The International Journal of Critical Infrastructure Protection (IJCIP) was launched in 2008, with the primary aim of publishing scholarly papers of the highest quality in all areas of critical infrastructure protection. Of particular interest are articles that weave science, technology, law and policy to craft sophisticated yet practical solutions for securing assets in the various critical infrastructure sectors. These critical infrastructure sectors include: information technology, telecommunications, energy, banking and finance, transportation systems, chemicals, critical manufacturing, agriculture and food, defense industrial base, public health and health care, national monuments and icons, drinking water and water treatment systems, commercial facilities, dams, emergency services, nuclear reactors, materials and waste, postal and shipping, and government facilities. Protecting and ensuring the continuity of operation of critical infrastructure assets are vital to national security, public health and safety, economic vitality, and societal wellbeing. The scope of the journal includes, but is not limited to: 1. Analysis of security challenges that are unique or common to the various infrastructure sectors. 2. Identification of core security principles and techniques that can be applied to critical infrastructure protection. 3. Elucidation of the dependencies and interdependencies existing between infrastructure sectors and techniques for mitigating the devastating effects of cascading failures. 4. Creation of sophisticated, yet practical, solutions, for critical infrastructure protection that involve mathematical, scientific and engineering techniques, economic and social science methods, and/or legal and public policy constructs.
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