智慧電網中的資訊保護問題日趨重要，除了探討防護方法外，部分學者則是探討攻擊方式。其中最具代表的即為假數據注入攻擊(false data injection attack, FDIA)，而後有人提出利用主成分分析做進階的假數據注入攻擊─不需得知此電力系統的架構且電力系統的狀態訊號為任意分布。然而此方法依舊有部分條件限制，如電力系統須為直流狀態估測，不得為交流狀態估測，這限制了它的應用。本篇論文嘗試提出能應用在交流狀態估測的攻擊方法，利用迴歸分析搭配廣義反矩陣找出電力系統量測資料的變化資訊，並使用此資訊達到注入隨機數據攻擊的目的。此方法只需要分析一段時間的量測值以產生有效的攻擊，不需要事先取得受到極為嚴密保護的電力系統架構資料，減少產生攻擊所需的時間和成本。

The information protection issues are becoming increasingly important in smart grid. In addition to explore the protective methods, some scholars explore attacking methods. One of the most representative of those methods is the false data injection attacks (false data injection attack, FDIA). Someone suggested that the use of principal component analysis for the advanced false data injection attacks─do not need to know the architecture of the power system and the status of signal is arbitrary distribution. However, this method is still has some limitations, such as DC power system state estimation shall not be for the exchange of AC power system state estimation, which limits its application. This paper tries to put forward a kind of attack that can be applied in AC state estimation. Regression analysis with pseudo-inverse method is used to identify changes in the power system measurement data, and use this information to achieve the purpose of injecting random data attacks. The proposed method doesn’t require the architecture data of the power system. Intruders only need to obtain a period of time’s measurement data. That makes the attack becomes more easily to produce because the protection of architecture data is harder than the protection of measurement data.

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