关键词: 低秩表示, 数据挖掘, 网络空间安全, 电力状态估计

Abstract: Smart grid plays a critical role in national production. The stability and security of smart grid is essentially important. As a result, it is significant to detect the bad and malicious data from daily observations. This paper proposes a novel outlier detection method based on low-rank representation. Specifically, the observation is decomposed into two parts：a low-rank part for clean data and a sparse part for outliers. In addition, this paper deploys ALM（Augmented Lagrange Multiplier） to optimize the objective. Extensive experiments on two popular benchmarks verify the advantages of the proposed method.

Key words: low-rank representation, data mining, cyberspace security, power state estimation