Deeply Hidden Moving-Target-Defense for Cybersecure Unbalanced Distribution Systems Considering Voltage Stability

A recent proactive defense mechanism, named as moving-target-defense (MTD), has been proposed as a prevailing topic that is capable of actively changing transmission line reactance to preclude cyberattacks. However, cyberattacks could significantly damage the operational stability, such as voltage stability, for the unbalanced distribution systems. Measurements may be tampered with multiple types of false data injection cyberattacks. Towards the end, this paper proposes a deeply hidden MTD (DH-MTD) to elaborately hide both the self and mutual reactance of each phase at the transmission line installed with D-FACTS devices. Both the branch and injection power phasor measurement functions are integrated into DH-MTD in the cyberattack scenario and under the normal operating condition, while the system voltage stability is ensured. The proposed DH-MTD model is solved using a nonlinear least square (NLS) method based on the trust-region algorithm due to the non-Gaussian noise assumption. Also, we cope with the MTD allocation (MTDA) problem using a data-driven normalized PDF peak residual (NPPR) index. The effectiveness of the proposed DHMTD method is demonstrated in the unbalanced IEEE 123-bus distribution system against both branch and node cyberattacks. False data injection attacks, including scaling, ramping, random, and smooth-curve attacks, can be successfully prevented.