Of the range of wireless communication technologies, wireless sensor networks (WSN) will be one of the most appropriate technologies for the Microgrid and Grid-enabled Vehicles in the Smartgrid. To ensure the security of WSN, the detection of attacks is more efficient than their prevention because of the lack of computing power. Malicious packet drops are the easiest means of attacking WSNs. Thus, the sensors used for constructing a WSN require a packet drop monitoring agent, such as Watchdog. However, Watchdog has a partial drop problem such that an attacker can manipulate the packet dropping rate below the minimum misbehaviour monitoring threshold. Furthermore, Watchdog does not consider real traffic situations, such as congestion and collision, and so it has no way of recognizing whether a packet drop is due to a real attack or network congestion. In this paper, we propose a malicious packet drop monitoring agent, which considers traffic conditions. We used the actual traffic volume on neighbouring nodes and the drop rate while monitoring a sending node for specific period. It is more effective in real network scenarios because unlike Watchdog it considers the actual traffic, which only uses the Pathrater. Moreover, our proposed method does not require authentication, packet encryption or detection packets. Thus, there is a lower likelihood of detection failure due to packet spoofing, Man-In-the Middle attacks or Wormhole attacks. To test the suitability of our proposed concept for a series of network scenarios, we divided the simulations into three types: one attack node, more than one attack nodes and no attack nodes. The results of the simulations meet our expectations.

SUMMARYSmart grid, known as the system of systems, has progressed with more diverse network systems than existing Internetbased networks. Although some of its internal components contain systems reminiscent of a general Internet environment, most of them have different characteristics in terms of their function and performance. Therefore, it is impractical to apply the same techniques for quantifying security vulnerabilities used in existing Internet environments to smart grid. Such techniques do not reflect the characteristics of smart grid networks. In addition, the existing quantification approaches to security vulnerability typically apply to vulnerabilities known in a target system itself or by generalizing attack paths that can occur in a target system. Therefore, it is difficult for these approaches to reflect the vulnerabilities in an environment such as smart grid, which has various heterogeneous systems and networks. In this paper, we consider various approaches to quantifying security vulnerabilities in smart grid network environments by analyzing the existing quantification approaches to security vulnerabilities, and we propose the smart grid network vulnerability score, a quantification approach to security vulnerability that can comprehensively display security threats by reflecting the characteristics of smart grid network. We verified the effectiveness and applicability of this proposed approach by applying it to the advanced metering infrastructure network, which is sensitive to the issues related to users in a number of smart grid network domains.

A smart grid is a large, consolidated electrical grid system that includes heterogeneous networks and systems. Based on the data, a smart grid system has a potential security threat in its network connectivity. To solve this problem, we develop and apply a novel scheme to measure the vulnerability in a smart grid domain. Vulnerability quantification can be the first step in security analysis because it can help prioritize the security problems. However, existing vulnerability quantification schemes are not suitable for smart grid because they do not consider network vulnerabilities. We propose a novel attack route-based vulnerability quantification scheme using a network vulnerability score and an end-to-end security score, depending on the specific smart grid network environment to calculate the vulnerability score for a particular attack route. To evaluate the proposed approach, we derive several attack scenarios from the advanced metering infrastructure domain. The experimental results of the proposed approach and the existing common vulnerability scoring system clearly show that we need to consider network connectivity for more optimized vulnerability quantification.

Security vulnerability quantification is the method that identify potential vulnerabilities by scoring vulnerabilities themselves and their countermeasures. However, due to the structural feature of smart grid system, it is difficult to apply existing security threat evaluation schemes. In this paper, we propose a network model to evaluate smartgrid security threat for AMI and derive attack scenarios. Additionally, we show that the result of security threat evaluation for proposed network model and attack scenario by applying MTTC scheme.

SUMMARYWith the proliferation of smart grids and the construction of various electric IT systems and networks, a next-generation substation automation system (SAS) based on IEC 61850 has been agreed upon as a core element of smart grids. However, research on security vulnerability analysis and quantification for automated substations is still in the preliminary phase. In particular, it is not suitable to apply existing security vulnerability quantification approaches to IEC 61850-based SAS because of its heterogeneous characteristics. In this paper, we propose an IEC 61850-based SAS network modeling and evaluation approach for security vulnerability quantification. The proposed approach uses network-level and device groupings to categorize the characteristic of the SAS. In addition, novel attack scenarios are proposed through a zoning scheme to evaluate the network model. Finally, an MTTC (Mean Time-to-Compromise) scheme is used to verify the proposed network model using a sample attack scenario.