# Microgrid Cyber-Security: Review and Challenges toward Resilience
## 4 Perspective-Based Interventions Addressing Cyber Attacks
### Co-Simulation Testbeds  
Experimental studies are still economically unfeasible for microgrids, as it is for large-scale smart grids. With only a few reliable platforms around the world capable of performing highly complicated tests, real-time simulation is a powerful alternative solution in this area of research [37].  
Models running on this mode of simulation adhere to a very small step size in order to achieve an accurate result. Bypassing the right step size to a larger value produces an erroneous simulation while smaller values do not fit into the simulator constraints. This, in turn, creates a challenge, especially with models with high-speed switching devices [37]. The large number of switching devices is not the only source of trouble in simulating power systems. Broadly, the integrated power electronics devices in the smart grid simulation also tolerate high-frequency pulse width modulation signals, and that what explains the shift from traditional offline simulators that are time-consuming and not adjusted for slow phenomena [59].  
Additional complications come to the surface concerning the representation of the cyber-physical components in the same computational environment. The inhomogeneous nature of both power and communication systems plus the obvious differences in components, transmission content, and working mechanisms make it very challenging to accommodate the desired realistic features in one frame. For instance, the time-varying or continuous solvers suit the power systems while communication networks' simulation necessitate a discrete or event-dependent simulation [60]. In other words, the behavior of the grid control is mainly well defined using mathematical formulations, which is not exactly the case in the nearly stochastic, unpredictable data transmission protocol layer that belongs to the accompanying ICT system [61].  
Even when ending up finding the perfect tool to simulate each structure separately, interfacing the two simulators in a way that guarantees the integration of the distinct characteristics for both, without restraining the core to either of each is not always evident and often stipulates grappling with synchronization and data exchange.  
With all these obstacles, it seemed just right that some works had chosen to probe the different types of taxonomies of the existing testbeds since that discovering the various tools and techniques implemented in the current testbeds, counting also the strong and weak points for each one, is crucial to build and develop new experimental platforms.  
In this context, the term \"co-simulation\" refers to the practical and realistic co-existence of the examined subsystems whereupon they operate hand by hand to reflect smart grid interactions [62].  
The co-simulation development can take two directions; the first one primarily focuses on a specific tool that has been familiarly dealt with, in the course of studying individual subsystems. Researchers who seek this approach are usually more concerned in deepening their understanding of the interaction control between the intended subsystems. The second approach is a platform-based one which implies fixing the attention on the development of a comprehensive framework with a standardized interface capable of embracing different tools. This attracts researchers who deal with utterly complicated simulation environments, especially when flexibility in connecting the subsystem is inevitably expected, without intervening in neither layouts [61].