List of Articles false data injection attack

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  1 - Detection and Mitigation of a Combined Cyber Attack on Automatic Generation Control
  Tina Hajiabdollah H. Seifi Hamed Delkhosh
  Recent advances in power system monitoring and control require communication infrastructure to send and receive measurement data and control commands. These cyber-physical interactions, despite increasing efficiency and reliability, have exposed power systems to cyber a More

  Recent advances in power system monitoring and control require communication infrastructure to send and receive measurement data and control commands. These cyber-physical interactions, despite increasing efficiency and reliability, have exposed power systems to cyber attacks. The Automatic Generation Control (AGC) is one of the most important control systems in the power system, which requires communication infrastructure and has been highly regarded by cyber attackers. Since a successful attack on the AGC, not only has a direct impact on the system frequency, but can also affect the stability and economic performance of the power system. Therefore, understanding the impact of cyber attacks on AGC and developing strategies to defend against them have necessity and research importance. In most of the research in the field of attack-defense of AGC, the limitations of AGC in modeling such as governor dead band and communication network transmission delay have been ignored. On the other hand, considering two cyber attacks on the AGC and proposing a way to defend against them simultaneously, have not been considered. In this paper, while using the improved AGC model including governor dead band and communication network transmission delay, the effect of two attacks - data injection attack (FDI) and delay attack which are the most important cyber attacks on AGC - has been investigated. Also, the simultaneous effect of these two attacks is discussed as a combined cyber attack. The Kalman filter-based three-step defense method has been proposed to detect, estimate and mitigate the impact of the attacks and its effectiveness has been tested on the two-area AGC system. Manuscript profile
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  2 - Robust Planning of False Data Injection Attack on Electricity Markets in Smart Grids
  Hamed Badrsimaei R. Hooshmand Soghra  Nobakhtian
  False data injection attack (FDIA) is a destructive cyber threat to the economic performance of electricity markets in smart grids. A cyber attacker can make a huge financial profit by implementing an FDIA through penetrating the virtual transactions of the electricity More

  False data injection attack (FDIA) is a destructive cyber threat to the economic performance of electricity markets in smart grids. A cyber attacker can make a huge financial profit by implementing an FDIA through penetrating the virtual transactions of the electricity markets and manipulating electricity prices. In this paper, a new approach to planning an absolutely stealthily FDIA is presented with the aim of achieving maximum financial profit from the perspective of a cyber attacker participating in virtual transactions from two markets of day-ahead (DA) and real-time (RT). A common hypothesis in studies of FDIAs against electricity markets is that the attacker has complete information about the smart grid. But the fact is that the attacker has limited resources and can hardly access all the network information. This paper proposes a robust approach in designing an attack strategy under incomplete network information conditions. In particular, it is assumed that the attacker has uncertainties about the network modeling matrices. The validity of the proposed method is evaluated based on the IEEE 14-bus standard system using the Matpower tool. Numerical results confirm the relative success of the proposed attack in cases of varying degrees of incomplete information. Manuscript profile