Intrusion Detection Systems (IDSs) are an essential element of modern cyber defense,
alerting users to when and where cyber-attacks occur. Machine learning can enable IDSs to …

Machine learning (ML) sees an increasing prevalence of being used in the Internet of Things
(IoT)-based smart grid. However, the trustworthiness of ML is a severe issue that must be …

A massive challenge for future cities is being environmentally sustainable by incorporating
renewable energy resources (RES). At the same time, future smart cities need to support …

Precise electric load forecasting at different time horizons is an essential aspect for electricity
producers and consumers who participate in energy markets in order to maximize their …

Detecting and characterizing malicious operations in electricity markets presents substantial
challenges due to the innate complexity of power networks. This paper explores adversarial …

False data injection attacks (FDIAs) are a real and latent threat in modern power systems
networks due to the unprecedented integration of data acquisition systems. It is of utmost …

随着新型能源互联网的发展, 大规模的传感量测系统为基于数据驱动的虚假数据注入攻击检测
方法提供了数据支持, 然而攻击样本数据不平衡问题会影响此类方法的性能 …

As power big data plays an increasingly important role in the operation, maintenance, and
management of power systems, complex and covert false data attacks pose a serious threat …

This article proposes a distributed false data injection attack (FDIA) by attacking to the
boundary buses in an interconnected power system. The proposed attack utilizes the …

The smart grid, which is critical for developing smart cities, has a tool called state estimation
(SE), which enables operators to monitor the system's stability. While the SE result is …