## 1 Introduction
The cascading-failure-based AC power flow model proposed in this paper improves the simulation of voltage-related failures in the grid under uncertainty. In the literature [21; 22; 23]; computational intelligence methods have been utilized to minimize the time consumption of prior techniques. Reference [21] makes capital out of the cloud method to satisfy the accuracy in vulnerability assessment. In other words, the security scheme proposed in [21] using the vulnerability assessment could deal with the main security issues. On the other hand, structured approaches like network analysis methods based on power-flow are still up to date. The researchers in reference [22] have utilized the DC power flow for computing the grid vulnerability. In this paper, using a new index based on the time-sequential Monte Carlo simulation and an N-k\({}^{\prime}\)-1 scenario, the reliability and vulnerability were evaluated and it was proven that the AC power flow can be privileged. In addition, reference [23] has designed and implemented an attacker-defender bi-level linear program for vulnerability assessment. In the other classification of the literature, surveys related to the network vulnerable points, effective vulnerability mitigation methods have been focused on ensuring reliability and resiliency of the grid. In the context of applications to strengthen power grid ability and prevent consequential accidents, many attempts have been made by industrial initiatives [24; 25], supervisory mechanisms [26], load reduction techniques [27], and employment of energy storage [28]. This investigation employs microgrids for vulnerability mitigation. In addition, it may be an important point of view that network vulnerability can be utilized as a significant criterion for evaluating the impact of cyber-attacks as well. As already mentioned, to deal with the destructive effects of cyber-attacks in network vulnerability points, the multi-layer cyber-security protocol is applied in this research. The first layer is a public security protocol based on blockchain. Blockchain technology has emerged in the economic environment, healthcare centers, and industry because of its remarkable advantages. The applicability of blockchain technology in tasks including voting, identity recognition, and data authenticity identification has brightened the concept of internet-of-things (IOT) in recent years. The blockchain platform is basically a security infrastructure based on the P2P networks without role-playing any governor, which guarantees the ultimate transactions [28]. The second one is the Reinforcement Learning (RL) method as the subset of machine learning techniques. Note that the detection of the vulnerable points can be considered from an attacker's view as well, in which the target would be to define the attacking strategies to get the maximum possible destruction within the power grid. Such an issue can be especially useful in network vulnerability analysis, that is, with the aim of recognizing the worst possible destruction an attacker may insert into the grid. Hence one can execute essential precautions. Several investigate vulnerability surveys using RL as in [29] for false data injection (FDI) attacks and [30] for consecutive grid topology attacks. Some explanations need to be described for the type of cyber-attacks described here. As expressed in reference [31], considering the basic structure and approach of both the blockchain technology and the RL method, it is expected that the proposed framework can be acceptably able to cover attack types related to unauthorized access, interception, distributed denial of service (DDOS) and the balanced attack. To realize the challenges expressed in this paper, Table 1 shows the main differences between the recent investigations and the suggested approach in detail [7; 26; 32; 33; 34]. As it can be seen, the authors in [31] have tried to provide a security platform for the smart grid without considering the network's vulnerable points.