NDLI: Threat From Being Social: Vulnerability Analysis of Social Network Coupled Smart Grid

Content Provider	Directory of Open Access Journals (DOAJ)
Author	Tianyi Pan Subhankar Mishra Lan N. Nguyen Gunhee Lee Jungmin Kang Jungtaek Seo My T. Thai
Abstract	Social networks (SNs) have been gradually applied by utility companies as an addition to smart grid and are proved to be helpful in smoothing load curves and reducing energy usage. However, SNs also bring in new threats to smart grid: misinformation in SNs may cause smart grid users to alter their demand, resulting in transmission line overloading and in turn leading to catastrophic impact to the grid. In this paper, we discuss the interdependence in the SN coupled smart grid and focus on its vulnerability. That is, how much can the smart grid be damaged when misinformation related to it diffuses in SNs? To analytically study the problem, we propose the misinformation attack problem in social-smart grid that identifies the top critical nodes in the SN, such that the smart grid can be greatly damaged when misinformation propagates from those nodes. This problem is challenging as we have to incorporate the complexity of the two networks concurrently. Nevertheless, we propose a technique that can explicitly take into account information diffusion in SN, power flow balance, and cascading failure in smart grid integratedly when evaluating node criticality, based on which we propose various strategies in selecting the most critical nodes. Also, we introduce controlled load shedding as a protection strategy to reduce the impact of cascading failure. The effectiveness of our algorithms is demonstrated by experiments on the IEEE bus test cases as well as the Pegase data set.
e-ISSN	21693536
DOI	10.1109/ACCESS.2017.2738565
Journal	IEEE Access
Volume Number	5
Language	English
Publisher	IEEE
Publisher Date	2017-01-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Electrical Engineering. Electronics. Nuclear Engineering Social Network Smart Grid Cascading Failure Interdependent Networks Power Grid
Content Type	Text
Resource Type	Article

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