Assessing and augmenting SCADA cyber security: a survey of techniques

SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

Multi-Layer Cyber-Physical Security and Resilience for Smart Grid

The smart grid is a large-scale complex system that integrates communication technologies with the physical layer operation of the energy systems. Security and resilience mechanisms by design are important to provide guarantee operations for the system. This chapter provides a layered perspective of the smart grid security and discusses game and decision theory as a tool to model the interactions among system components and the interaction between attackers and the system. We discuss game-theoretic applications and challenges in the design of cross-layer robust and resilient controller, secure network routing protocol at the data communication and networking layers, and the challenges of the information security at the management layer of the grid. The chapter will discuss the future directions of using game-theoretic tools in addressing multi-layer security issues in the smart grid.Comment: 16 page

Micro Smart Micro-grid and Its Cyber Security Aspects in a Port Infrastructure

Maritime ports are intensive energy areas with a plenty of electrical systems that require an average power of many tens of megawatts (MW). Competitiveness, profits, reduction of pollution, reliability of operations, carbon emission trading are important energy related considerations for any port authority. Current technology allows the deployment of a local micro-grid of the size of tenths of MW, capable of islanded operation in case of emergency and to grant an increasing energy independency. Ownership of the grid permits a large flexibility on prices of energy sold inside the port, trading on local electric market and reduction of pollution. Renewable energy generation has a large impact on costs since features a low marginal cost. Unfortunately the smart grid is a critical asset within the port infrastructure and its intelligence is a high-level target for cyberattacks. Such attacks are often based on malicious software (malware), which makes use of a controlling entity on the network to coordinate and propagate. In this document, we will outline some features of a port smart grid and typical characteristics of cyber-attacks including potential ways to recognize it and suggestion for effective countermeasures

Analysis of new control applications

This document reports the results of the activities performed during the first year of the CRUTIAL project, within the Work Package 1 "Identification and description of Control System Scenarios". It represents the outcome of the analysis of new control applications in the Power System and the identification of critical control system scenarios to be explored by the CRUTIAL project

ICT aspects of power systems and their security

This report provides a deep description of four complex Attack Scenarios that have as final goal to produce damage to the Electric Power Transmission System. The details about protocols used, vulnerabilities, devices etc. have been for obvious reasons hidden, and the ones presented have to be understood as mere (even if realistic) simplified versions of possible power systems.JRC.DG.G.6-Security technology assessmen

Using Reputation Based Trust to Overcome Malfunctions and Malicious Failures in Electric Power Protection Systems

This dissertation advocates the use of reputation-based trust in conjunction with a trust management framework based on network flow techniques to form a trust management toolkit (TMT) for the defense of future Smart Grid enabled electric power grid from both malicious and non-malicious malfunctions. Increases in energy demand have prompted the implementation of Smart Grid technologies within the power grid. Smart Grid technologies enable Internet based communication capabilities within the power grid, but also increase the grid\u27s vulnerability to cyber attacks. The benefits of TMT augmented electric power protection systems include: improved response times, added resilience to malicious and non-malicious malfunctions, and increased reliability due to the successful mitigation of detected faults. In one simulated test case, there was a 99% improvement in fault mitigation response time. Additional simulations demonstrated the TMT\u27s ability to determine which nodes were compromised and to work around the faulty devices when responding to transient instabilities. This added resilience prevents outages and minimizes equipment damage from network based attacks, which also improves system\u27s reliability. The benefits of the TMT have been demonstrated using computer simulations of dynamic power systems in the context of backup protection systems and special protection systems

Cybersecurity in Power Grids: Challenges and Opportunities

Increasing volatilities within power transmission and distribution force power grid operators to amplify their use of communication infrastructure to monitor and control their grid. The resulting increase in communication creates a larger attack surface for malicious actors. Indeed, cyber attacks on power grids have already succeeded in causing temporary, large-scale blackouts in the recent past. In this paper, we analyze the communication infrastructure of power grids to derive resulting fundamental challenges of power grids with respect to cybersecurity. Based on these challenges, we identify a broad set of resulting attack vectors and attack scenarios that threaten the security of power grids. To address these challenges, we propose to rely on a defense-in-depth strategy, which encompasses measures for (i) device and application security, (ii) network security, and (iii) physical security, as well as (iv) policies, procedures, and awareness. For each of these categories, we distill and discuss a comprehensive set of state-of-the art approaches, as well as identify further opportunities to strengthen cybersecurity in interconnected power grids

Demand-Side Threats to Power Grid Operations from IoT-Enabled Edge

The growing adoption of Internet-of-Things (IoT)-enabled energy smart appliances (ESAs) at the consumer end, such as smart heat pumps, electric vehicle chargers, etc., is seen as key to enabling demand-side response (DSR) services. However, these smart appliances are often poorly engineered from a security point of view and present a new threat to power grid operations. They may become convenient entry points for malicious parties to gain access to the system and disrupt important grid operations by abruptly changing the demand. Unlike utility-side and SCADA assets, ESAs are not monitored continuously due to their large numbers and the lack of extensive monitoring infrastructure at consumer sites. This article presents an in-depth analysis of the demand side threats to power grid operations including (i) an overview of the vulnerabilities in ESAs and the wider risk from the DSR ecosystem and (ii) key factors influencing the attack impact on power grid operations. Finally, it presents measures to improve the cyber-physical resilience of power grids, putting them in the context of ongoing efforts from the industry and regulatory bodies worldwide

Machine Learning Based Detection of False Data Injection Attacks in Wide Area Monitoring Systems

The Smart Grid (SG) is an upgraded, intelligent, and a more reliable version of the traditional Power Grid due to the integration of information and communication technologies. The operation of the SG requires a dense communication network to link all its components. But such a network renders it prone to cyber attacks jeopardizing the integrity and security of the communicated data between the physical electric grid and the control centers. One of the most prominent components of the SG are Wide Area Monitoring Systems (WAMS). WAMS are a modern platform for grid-wide information, communication, and coordination that play a major role in maintaining the stability of the grid against major disturbances. In this thesis, an anomaly detection framework is proposed to identify False Data Injection (FDI) attacks in WAMS using different Machine Learning (ML) and Deep Learning (DL) techniques, i.e., Deep Autoencoders (DAE), Long-Short Term Memory (LSTM), and One-Class Support Vector Machine (OC-SVM). These algorithms leverage diverse, complex, and high-volume power measurements coming from communications between different components of the grid to detect intelligent FDI attacks. The injected false data is assumed to target several major WAMS monitoring applications, such as Voltage Stability Monitoring (VSM), and Phase Angle Monitoring (PAM). The attack vector is considered to be smartly crafted based on the power system data, so that it can pass the conventional bad data detection schemes and remain stealthy. Due to the lack of realistic attack data, machine learning-based anomaly detection techniques are used to detect FDI attacks. To demonstrate the impact of attacks on the realistic WAMS traffic and to show the effectiveness of the proposed detection framework, a Hardware-In-the-Loop (HIL) co-simulation testbed is developed. The performance of the implemented techniques is compared on the testbed data using different metrics: Accuracy, F1 score, and False Positive Rate (FPR) and False Negative Rate (FNR). The IEEE 9-bus and IEEE 39-bus systems are used as benchmarks to investigate the framework scalability. The experimental results prove the effectiveness of the proposed models in detecting FDI attacks in WAMS