A Tale of Two Industroyers: It was the Season of Darkness

In this paper, we study two pieces of malware that attempted to create blackouts in Ukraine. In particular, we design and develop a new sandbox that emulates different networks, devices, and other characteristics so that we can execute malware targeting substation equipment and understand in detail the specific sequence of actions the attackers could perform on substation equipment. We also study the effects that future similar malware can have. Our findings include new malware behavior not previously documented (such as the detailed algorithm for the MMS protocol payload) and an illustration of how attacking different targets will produce different effects

On the Detection of Cyber-Attacks in the Communication Network of IEC 61850 Electrical Substations

The availability of the data within the network communication remains one of the most critical requirement when compared to integrity and confidentiality. Several threats such as Denial of Service (DoS) or flooding attacks caused by Generic Object Oriented Substation Event (GOOSE) poisoning attacks, for instance, might hinder the availability of the communication within IEC 61850 substations. To tackle such threats, a novel method for the Early Detection of Attacks for the GOOSE Network Traffic (EDA4GNeT) is developed in the present work. Few of previously available intrusion detection systems take into account the specific features of IEC 61850 substations and offer a good trade-off between the detection performance and the detection time. Moreover, to the best of our knowledge, none of the existing works proposes an early anomaly detection method of GOOSE attacks in the network traffic of IEC 61850 substations that account for the specific characteristics of the network data in electrical substations. The EDA4GNeT method considers the dynamic behavior of network traffic in electrical substations. The mathematical modeling of the GOOSE network traffic first enables the development of the proposed method for anomaly detection. In addition, the developed model can also support the management of the network architecture in IEC 61850 substations based on appropriate performance studies. To test the novel anomaly detection method and compare the obtained results with available techniques, two use cases are used

Combined network intrusion and phasor data anomaly detection for secure dynamic control centers

The dynamic operation of power transmission systems requires the acquisition of reliable and accurate measurement and state information. The use of TCP/IP-based communication protocols such as IEEE C37.118 or IEC 61850 introduces different gateways to launch cyber-attacks and to compromise major system operation functionalities. Within this study, a combined network intrusion and phasor data anomaly detection system is proposed to enable a secure system operation in the presence of cyber-attacks for dynamic control centers. This includes the utilization of expert-rules, one-class classifiers, as well as recurrent neural networks to monitor different network packet and measurement information. The effectiveness of the proposed network intrusion and phasor data anomaly detection system is shown within a real-time simulation testbed considering multiple operation and cyber-attack conditions

Security Analysis of Phasor Measurement Units in Smart Grid Communication Infrastructures

Phasor Measurement Units (PMUs), or synchrophasors, are rapidly being deployed in the smart grid with the goal of measuring phasor quantities concurrently from wide area distribution substations. By utilizing GPS receivers, PMUs can take a wide area snapshot of power systems. Thus, the possibility of blackouts in the smart grid, the next generation power grid, will be reduced. As the main enabler of Wide Area Measurement Systems (WAMS), PMUs transmit measured values to Phasor Data Concentrators (PDCs) by the synchrophasor standard IEEE C37.118. IEC 61850 and IEC 62351 are the communication protocols for the substation automation system and the security standard for the communication protocol of IEC 61850, respectively. According to the aforementioned communication and security protocols, as well as the implementation constraints of different platforms, HMAC-SHA1 was suggested by the TC 57 WG group in October 2009. The hash-based Message Authentication Code (MAC) is an algorithm for verifying both message integrity and authentication by using an iterative hash function and a supplied secret key. There are a variety of security attacks on the PMU communications infrastructure. Timing Side Channel Attack (SCA) is one of these possible attacks. In this thesis, timing side channel vulnerability against execution time of the HMAC-SHA1 authentication algorithm is studied. Both linear and negative binomial regression are used to model some security features of the stored key, e.g., its length and Hamming weight. The goal is to reveal secret-related information based on leakage models. The results would mitigate the cryptanalysis process of an attacker. Adviser: Yi Qia

Enhancing Cyber-Resiliency of DER-based SmartGrid: A Survey

The rapid development of information and communications technology has enabled the use of digital-controlled and software-driven distributed energy resources (DERs) to improve the flexibility and efficiency of power supply, and support grid operations. However, this evolution also exposes geographically-dispersed DERs to cyber threats, including hardware and software vulnerabilities, communication issues, and personnel errors, etc. Therefore, enhancing the cyber-resiliency of DER-based smart grid - the ability to survive successful cyber intrusions - is becoming increasingly vital and has garnered significant attention from both industry and academia. In this survey, we aim to provide a systematical and comprehensive review regarding the cyber-resiliency enhancement (CRE) of DER-based smart grid. Firstly, an integrated threat modeling method is tailored for the hierarchical DER-based smart grid with special emphasis on vulnerability identification and impact analysis. Then, the defense-in-depth strategies encompassing prevention, detection, mitigation, and recovery are comprehensively surveyed, systematically classified, and rigorously compared. A CRE framework is subsequently proposed to incorporate the five key resiliency enablers. Finally, challenges and future directions are discussed in details. The overall aim of this survey is to demonstrate the development trend of CRE methods and motivate further efforts to improve the cyber-resiliency of DER-based smart grid.Comment: Submitted to IEEE Transactions on Smart Grid for Publication Consideratio

Network and System Management for the Security Monitoring of Microgrids using IEC 62351-7

Interest in adding renewable energy sources to the power grid has risen substantially in recent years. As a response to this growing interest, the deployment of microgrids capable of integrating renewable energy has become more widespread. Microgrids are independent power systems that deliver power from different kinds of Distributed Energy Resources (DERs) to local energy consumers more efficiently than the conventional power grid. The microgrid leverages advanced information and communication technologies for vital protection, monitoring, and control operations as well as for energy management. With the use of information technology comes the need to protect the microgrid information layer from cyberattacks that can impact critical microgrid power operations. In this research, a security monitoring system to detect cyberattacks against the microgrid, in near-real time, is designed and implemented. To achieve this, the system applies Network and System Management (NSM) for microgrid security monitoring, as specified by the IEC 62351-7 security standard for power systems. The specific contributions of this research are (i) an investigation on the suitability of NSM for microgrid security monitoring; (ii) the design and implementation of an NSM platform; (iii) the design and implementation of a security analytics framework for NSM based on deep learning models; (iv) the elaboration of a comprehensive microgrid simulation model deployed on a Hardware in the Loop (HIL) co-simulation framework; and (v) an experimental evaluation on the effectiveness and scalability of the NSM security monitoring platform for detection against microgrid attack scenarios, with a methodology being used to systematically generate the scenarios. The experimental results validate the usefulness of NSM in detecting attacks against the microgrid