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2020-07-10
Javed Butt, Usman, Abbod, Maysam, Lors, Anzor, Jahankhani, Hamid, Jamal, Arshad, Kumar, Arvind.  2019.  Ransomware Threat and its Impact on SCADA. 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3). :205—212.
Modern cybercrimes have exponentially grown over the last one decade. Ransomware is one of the types of malware which is the result of sophisticated attempt to compromise the modern computer systems. The governments and large corporations are investing heavily to combat this cyber threat against their critical infrastructure. It has been observed that over the last few years that Industrial Control Systems (ICS) have become the main target of Ransomware due to the sensitive operations involved in the day to day processes of these industries. As the technology is evolving, more and more traditional industrial systems are replaced with advanced industry methods involving advanced technologies such as Internet of Things (IoT). These technology shift help improve business productivity and keep the company's global competitive in an overflowing competitive market. However, the systems involved need secure measures to protect integrity and availability which will help avoid any malfunctioning to their operations due to the cyber-attacks. There have been several cyber-attack incidents on healthcare, pharmaceutical, water cleaning and energy sector. These ICS' s are operated by remote control facilities and variety of other devices such as programmable logic controllers (PLC) and sensors to make a network. Cyber criminals are exploring vulnerabilities in the design of these ICS's to take the command and control of these systems and disrupt daily operations until ransomware is paid. This paper will provide critical analysis of the impact of Ransomware threat on SCADA systems.
2020-07-06
Xiong, Leilei, Grijalva, Santiago.  2019.  N-1 RTU Cyber-Physical Security Assessment Using State Estimation. 2019 IEEE Power Energy Society General Meeting (PESGM). :1–5.
Real-time supervisory control and data acquisition (SCADA) systems use remote terminal units (RTUs) to monitor and manage the flow of power at electrical substations. As their connectivity to different utility and private networks increases, RTUs are becoming more vulnerable to cyber-attacks. Some attacks seek to access RTUs to directly control power system devices with the intent to shed load or cause equipment damage. Other attacks (such as denial-of-service) target network availability and seek to block, delay, or corrupt communications between the RTU and the control center. In the most severe case, when communications are entirely blocked, the loss of an RTU can cause the power system to become unobservable. It is important to understand how losing an RTU impacts the system state (bus voltage magnitudes and angles). The system state is determined by the state estimator and serves as the input to other critical EMS applications. There is currently no systematic approach for assessing the cyber-physical impact of losing RTUs. This paper proposes a methodology for N-1 RTU cyber-physical security assessment that could benefit power system control and operation. We demonstrate our approach on the IEEE 14-bus system as well as on a synthetic 200-bus system.
Castillo, Anya, Arguello, Bryan, Cruz, Gerardo, Swiler, Laura.  2019.  Cyber-Physical Emulation and Optimization of Worst-Case Cyber Attacks on the Power Grid. 2019 Resilience Week (RWS). 1:14–18.
In this paper we report preliminary results from the novel coupling of cyber-physical emulation and interdiction optimization to better understand the impact of a CrashOverride malware attack on a notional electric system. We conduct cyber experiments where CrashOverride issues commands to remote terminal units (RTUs) that are controlling substations within a power control area. We identify worst-case loss of load outcomes with cyber interdiction optimization; the proposed approach is a bilevel formulation that incorporates RTU mappings to controllable loads, transmission lines, and generators in the upper-level (attacker model), and a DC optimal power flow (DCOPF) in the lower-level (defender model). Overall, our preliminary results indicate that the interdiction optimization can guide the design of experiments instead of performing a “full factorial” approach. Likewise, for systems where there are important dependencies between SCADA/ICS controls and power grid operations, the cyber-physical emulations should drive improved parameterization and surrogate models that are applied in scalable optimization techniques.
2020-04-24
Serras, Paula, Ibarra-Berastegi, Gabriel, Saénz, Jon, Ulazia, Alain, Esnaola, Ganix.  2019.  Analysis of Wells-type turbines’ operational parameters during winter of 2014 at Mutriku wave farm. OCEANS 2019 – Marseille. :1—5.

Mutriku wave farm is the first commercial plant all around the world. Since July 2011 it has been continuously selling electricity to the grid. It operates with the OWC technology and has 14 operating Wells-type turbines. In the plant there is a SCADA data recording system that collects the most important parameters of the turbines; among them, the pressure in the inlet chamber, the position of the security valve (from fully open to fully closed) and the generated power in the last 5 minutes. There is also an electricity meter which provides information about the amount of electric energy sold to the grid. The 2014 winter (January, February and March), and especially the first fortnight of February, was a stormy winter with rough sea state conditions. This was reflected both in the performance of the turbines (high pressure values, up to 9234.2 Pa; low opening degrees of the security valve, down to 49.4°; and high power generation of about 7681.6 W, all these data being average values) and in the calculated capacity factor (CF = 0.265 in winter and CF = 0.294 in February 2014). This capacity factor is a good tool for the comparison of different WEC technologies or different locations and shows an important seasonal behavior.

2020-03-16
Babay, Amy, Schultz, John, Tantillo, Thomas, Beckley, Samuel, Jordan, Eamon, Ruddell, Kevin, Jordan, Kevin, Amir, Yair.  2019.  Deploying Intrusion-Tolerant SCADA for the Power Grid. 2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). :328–335.
While there has been considerable research on making power grid Supervisory Control and Data Acquisition (SCADA) systems resilient to attacks, the problem of transitioning these technologies into deployed SCADA systems remains largely unaddressed. We describe our experience and lessons learned in deploying an intrusion-tolerant SCADA system in two realistic environments: a red team experiment in 2017 and a power plant test deployment in 2018. These experiences resulted in technical lessons related to developing an intrusion-tolerant system with a real deployable application, preparing a system for deployment in a hostile environment, and supporting protocol assumptions in that hostile environment. We also discuss some meta-lessons regarding the cultural aspects of transitioning academic research into practice in the power industry.
Mercaldo, Francesco, Martinelli, Fabio, Santone, Antonella.  2019.  Real-Time SCADA Attack Detection by Means of Formal Methods. 2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE). :231–236.
SCADA control systems use programmable logic controller to interface with critical machines. SCADA systems are used in critical infrastructures, for instance, to control smart grid, oil pipelines, water distribution and chemical manufacturing plants: an attacker taking control of a SCADA system could cause various damages, both to the infrastructure but also to people (for instance, adding chemical substances into a water distribution systems). In this paper we propose a method to detect attacks targeting SCADA systems. We exploit model checking, in detail we model logs from SCADA systems into a network of timed automata and, through timed temporal logic, we characterize the behaviour of a SCADA system under attack. Experiments performed on a SCADA water distribution system confirmed the effectiveness of the proposed method.
Ren, Wenyu, Yu, Tuo, Yardley, Timothy, Nahrstedt, Klara.  2019.  CAPTAR: Causal-Polytree-based Anomaly Reasoning for SCADA Networks. 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). :1–7.
The Supervisory Control and Data Acquisition (SCADA) system is the most commonly used industrial control system but is subject to a wide range of serious threats. Intrusion detection systems are deployed to promote the security of SCADA systems, but they continuously generate tremendous number of alerts without further comprehending them. There is a need for an efficient system to correlate alerts and discover attack strategies to provide explainable situational awareness to SCADA operators. In this paper, we present a causal-polytree-based anomaly reasoning framework for SCADA networks, named CAPTAR. CAPTAR takes the meta-alerts from our previous anomaly detection framework EDMAND, correlates the them using a naive Bayes classifier, and matches them to predefined causal polytrees. Utilizing Bayesian inference on the causal polytrees, CAPTAR can produces a high-level view of the security state of the protected SCADA network. Experiments on a prototype of CAPTAR proves its anomaly reasoning ability and its capabilities of satisfying the real-time reasoning requirement.
Al Ghazo, Alaa T., Kumar, Ratnesh.  2019.  ICS/SCADA Device Recognition: A Hybrid Communication-Patterns and Passive-Fingerprinting Approach. 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). :19–24.
The Industrial Control System (ICS) and Supervisory Control and Data Acquisition (SCADA) systems are the backbones for monitoring and supervising factories, power grids, water distribution systems, nuclear plants, and other critical infrastructures. These systems are installed by third party contractors, maintained by site engineers, and operate for a long time. This makes tracing the documentation of the systems' changes and updates challenging since some of their components' information (type, manufacturer, model, etc.) may not be up-to-date, leading to possibly unaccounted security vulnerabilities in the systems. Device recognition is useful first step in vulnerability identification and defense augmentation, but due to the lack of full traceability in case of legacy ICS/SCADA systems, the typical device recognition based on document inspection is not applicable. In this paper, we propose a hybrid approach involving the mix of communication-patterns and passive-fingerprinting to identify the unknown devices' types, manufacturers, and models. The algorithm uses the ICS/SCADA devices's communication-patterns to recognize the control hierarchy levels of the devices. In conjunction, certain distinguishable features in the communication-packets are used to recognize the device manufacturer, and model. We have implemented this hybrid approach in Python, and tested on traffic data from a water treatment SCADA testbed in Singapore (iTrust).
Sharma, Neha, Ramachandran, Ramkumar Ketti.  2019.  Security challenges for Water Distribution System Using Supervisory Control and Data Acquisition (SCADA). 2019 Fifth International Conference on Image Information Processing (ICIIP). :234–239.
In the distributed Supervisory Control and Data Acquisitions (SCADA) system there is a need of doing the acquisition of very large amount of data on the network to visualize the same process in realtime or in the future. Water is distributed automatically to large area through autonomous SCADA systems. This makes the systems prone to various attacks at different instances and levels. The SCADA systems are also used for distributing common resources that range from Gas, Electricity, and Water distribution. It is the need of the hour to work on the security issues of such distribution systems to provide hassle-free services. This paper reviews the major problems on the water distribution system and possible attacks that are harmful during data acquisition and transfer. This paper also gives the insight on the latest technologies like elastic search and data modelling to increase the security of the water distribution system.
Radoglou-Grammatikis, Panagiotis, Sarigiannidis, Panagiotis, Giannoulakis, Ioannis, Kafetzakis, Emmanouil, Panaousis, Emmanouil.  2019.  Attacking IEC-60870-5-104 SCADA Systems. 2019 IEEE World Congress on Services (SERVICES). 2642-939X:41–46.
The rapid evolution of the Information and Communications Technology (ICT) services transforms the conventional electrical grid into a new paradigm called Smart Grid (SG). Even though SG brings significant improvements, such as increased reliability and better energy management, it also introduces multiple security challenges. One of the main reasons for this is that SG combines a wide range of heterogeneous technologies, including Internet of Things (IoT) devices as well as Supervisory Control and Data Acquisition (SCADA) systems. The latter are responsible for monitoring and controlling the automatic procedures of energy transmission and distribution. Nevertheless, the presence of these systems introduces multiple vulnerabilities because their protocols do not implement essential security mechanisms such as authentication and access control. In this paper, we focus our attention on the security issues of the IEC 60870-5-104 (IEC-104) protocol, which is widely utilized in the European energy sector. In particular, we provide a SCADA threat model based on a Coloured Petri Net (CPN) and emulate four different types of cyber attacks against IEC-104. Last, we used AlienVault's risk assessment model to evaluate the risk level that each of these cyber attacks introduces to our system to confirm our intuition about their severity.
Yadav, Geeta, Paul, Kolin.  2019.  Assessment of SCADA System Vulnerabilities. 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). :1737–1744.
SCADA system is an essential component for automated control and monitoring in many of the Critical Infrastructures (CI). Cyber-attacks like Stuxnet, Aurora, Maroochy on SCADA systems give us clear insight about the damage a determined adversary can cause to any country's security, economy, and health-care systems. An in-depth analysis of these attacks can help in developing techniques to detect and prevent attacks. In this paper, we focus on the assessment of SCADA vulnerabilities from the widely used National Vulnerability Database (NVD) until May 2019. We analyzed the vulnerabilities based on severity, frequency, availability, integrity and confidentiality impact, and Common Weaknesses. The number of reported vulnerabilities are increasing yearly. Approximately 89% of the attacks are the network exploits severely impacting availability of these systems. About 19% of the weaknesses are due to buffer errors due to the use of insecure and legacy operating systems. We focus on finding the answer to four key questions that are required for developing new technologies for securing SCADA systems. We believe this is the first study of its kind which looks at correlating SCADA attacks with publicly available vulnerabilities. Our analysis can provide security researchers with useful insights into SCADA critical vulnerabilities and vulnerable components, which need attention. We also propose a domain-specific vulnerability scoring system for SCADA systems considering the interdependency of the various components.
Yang, Huan, Cheng, Liang, Chuah, Mooi Choo.  2019.  Deep-Learning-Based Network Intrusion Detection for SCADA Systems. 2019 IEEE Conference on Communications and Network Security (CNS). :1–7.
Supervisory Control and Data Acquisition (SCADA)networks are widely deployed in modern industrial control systems (ICSs)such as energy-delivery systems. As an increasing number of field devices and computing nodes get interconnected, network-based cyber attacks have become major cyber threats to ICS network infrastructure. Field devices and computing nodes in ICSs are subjected to both conventional network attacks and specialized attacks purposely crafted for SCADA network protocols. In this paper, we propose a deep-learning-based network intrusion detection system for SCADA networks to protect ICSs from both conventional and SCADA specific network-based attacks. Instead of relying on hand-crafted features for individual network packets or flows, our proposed approach employs a convolutional neural network (CNN)to characterize salient temporal patterns of SCADA traffic and identify time windows where network attacks are present. In addition, we design a re-training scheme to handle previously unseen network attack instances, enabling SCADA system operators to extend our neural network models with site-specific network attack traces. Our results using realistic SCADA traffic data sets show that the proposed deep-learning-based approach is well-suited for network intrusion detection in SCADA systems, achieving high detection accuracy and providing the capability to handle newly emerged threats.
Eneh, Joy Nnenna, Onyekachi Orah, Harris, Emeka, Aka Benneth.  2019.  Improving the Reliability and Security of Active Distribution Networks Using SCADA Systems. 2019 IEEE PES/IAS PowerAfrica. :110–115.
The traditional electricity distribution system is rapidly shifting from the passive infrastructure to a more active infrastructure, giving rise to a smart grid. In this project an active electricity distribution network and its components have been studied. A 14-node SCADA-based active distribution network model has been proposed for managing this emerging network infrastructure to ensure reliability and protection of the network The proposed model was developed using matlab /simulink software and the fuzzy logic toolbox. Surge arresters and circuit breakers were modelled and deployed in the network at different locations for protection and isolation of fault conditions. From the reliability analysis of the proposed model, the failure rate and outage hours were reduced due to better response of the system to power fluctuations and fault conditions.
Lin, Kuo-Sui.  2019.  A New Evaluation Model for Information Security Risk Management of SCADA Systems. 2019 IEEE International Conference on Industrial Cyber Physical Systems (ICPS). :757–762.
Supervisory control and data acquisition (SCADA) systems are becoming increasingly susceptible to cyber-physical attacks on both physical and cyber layers of critical information infrastructure. Failure Mode and Effects Analysis (FMEA) have been widely used as a structured method to prioritize all possible vulnerable areas (failure modes) for design review of security of information systems. However, traditional RPN based FMEA has some inherent problems. Besides, there is a lacking of application of FMEA for security in SCADAs under vague and uncertain environment. Thus, the main purpose of this study was to propose a new evaluation model, which not only intends to recover above mentioned problems, but also intends to evaluate, prioritize and correct security risk of SCADA system's threat modes. A numerical case study was also conducted to demonstrate that the proposed new evaluation model is not only capable of addressing FMEA's inherent problems but also is best suited for a semi-quantitative high level analysis of a secure SCADA's failure modes in the early design phases.
2020-02-17
Kim, Joonsoo, Kim, Kyeongho, Jang, Moonsu.  2019.  Cyber-Physical Battlefield Platform for Large-Scale Cybersecurity Exercises. 2019 11th International Conference on Cyber Conflict (CyCon). 900:1–19.
In this study, we propose a platform upon which a cyber security exercise environment can be built efficiently for national critical infrastructure protection, i.e. a cyber-physical battlefield (CPB), to simulate actual ICS/SCADA systems in operation. Among various design considerations, this paper mainly discusses scalability, mobility, reality, extensibility, consideration of the domain or vendor specificities, and the visualization of physical facilities and their damage as caused by cyber attacks. The main purpose of the study was to develop a platform that can maximize the coverage that encompasses such design considerations. We discuss the construction of the platform through the final design choices. The features of the platform that we attempt to achieve are closely related to the target cyber exercise format. Design choices were made considering the construction of a realistic ICS/SCADA exercise environment that meets the goals and matches the characteristics of the Cyber Conflict Exercise (CCE), an annual national exercise organized by the National Security Research Institute (NSR) of South Korea. CCE is a real-time attack-defense battlefield drill between 10 red teams who try to penetrate a multi-level organization network and 16 blue teams who try to defend the network. The exercise platform provides scalability and a significant degree of freedom in the design of a very large-scale CCE environment. It also allowed us to fuse techniques such as 3D-printing and augmented reality (AR) to achieve the exercise goals. This CPB platform can also be utilized in various ways for different types of cybersecurity exercise. The successful application of this platform in Locked Shields 2018 (LS18) is strong evidence of this; it showed the great potential of this platform to integrate high-level strategic or operational exercises effectively with low-level technical exercises. This paper also discusses several possible improvements of the platform which could be made for better integration, as well as various exercise environments that can be constructed given the scalability and extensibility of the platform.
2020-01-13
Kabiri, Peyman, Chavoshi, Mahdieh.  2019.  Destructive Attacks Detection and Response System for Physical Devices in Cyber-Physical Systems. 2019 International Conference on Cyber Security and Protection of Digital Services (Cyber Security). :1–6.

Nowadays, physical health of equipment controlled by Cyber-Physical Systems (CPS) is a significant concern. This paper reports a work, in which, a hardware is placed between Programmable Logic Controller (PLC) and the actuator as a solution. The proposed hardware operates in two conditions, i.e. passive and active. Operation of the proposed solution is based on the repetitive operational profile of the actuators. The normal operational profile of the actuator is fed to the protective hardware and is considered as the normal operating condition. In the normal operating condition, the middleware operates in its passive mode and simply monitors electronic signals passing between PLC and Actuator. In case of any malicious operation, the proposed hardware operates in its active mode and both slowly stops the actuator and sends an alert to SCADA server initiating execution of the actuator's emergency profile. Thus, the proposed hardware gains control over the actuator and prevents any physical damage on the operating devices. Two sample experiments are reported in which, results of implementing the proposed solution are reported and assessed. Results show that once the PLC sends incorrect data to actuator, the proposed hardware detects it as an anomaly. Therefore, it does not allow the PLC to send incorrect and unauthorized data pattern to its actuator. Significance of the paper is in introducing a solution to prevent destruction of physical devices apart from source or purpose of the encountered anomaly and apart from CPS functionality or PLC model and operation.

2019-12-02
Ibarra, Jaime, Javed Butt, Usman, Do, Anh, Jahankhani, Hamid, Jamal, Arshad.  2019.  Ransomware Impact to SCADA Systems and its Scope to Critical Infrastructure. 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3). :1–12.
SCADA systems are being constantly migrated to modern information and communication technologies (ICT) -based systems named cyber-physical systems. Unfortunately, this allows attackers to execute exploitation techniques into these architectures. In addition, ransomware insertion is nowadays the most popular attacking vector because it denies the availability of critical files and systems until attackers receive the demanded ransom. In this paper, it is analysed the risk impact of ransomware insertion into SCADA systems and it is suggested countermeasures addressed to the protection of SCADA systems and its components to reduce the impact of ransomware insertion.
Wang, Dinghua, Feng, Dongqin.  2018.  Intrusion Detection Model of SCADA Using Graphical Features. 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). :1208–1214.
Supervisory control and data acquisition system is an important part of the country's critical infrastructure, but its inherent network characteristics are vulnerable to attack by intruders. The vulnerability of supervisory control and data acquisition system was analyzed, combining common attacks such as information scanning, response injection, command injection and denial of service in industrial control systems, and proposed an intrusion detection model based on graphical features. The time series of message transmission were visualized, extracting the vertex coordinates and various graphic area features to constitute a new data set, and obtained classification model of intrusion detection through training. An intrusion detection experiment environment was built using tools such as MATLAB and power protocol testers. IEC 60870-5-104 protocol which is widely used in power systems had been taken as an example. The results of tests have good effectiveness.
2019-08-26
Gonzalez, D., Alhenaki, F., Mirakhorli, M..  2019.  Architectural Security Weaknesses in Industrial Control Systems (ICS) an Empirical Study Based on Disclosed Software Vulnerabilities. 2019 IEEE International Conference on Software Architecture (ICSA). :31–40.

Industrial control systems (ICS) are systems used in critical infrastructures for supervisory control, data acquisition, and industrial automation. ICS systems have complex, component-based architectures with many different hardware, software, and human factors interacting in real time. Despite the importance of security concerns in industrial control systems, there has not been a comprehensive study that examined common security architectural weaknesses in this domain. Therefore, this paper presents the first in-depth analysis of 988 vulnerability advisory reports for Industrial Control Systems developed by 277 vendors. We performed a detailed analysis of the vulnerability reports to measure which components of ICS have been affected the most by known vulnerabilities, which security tactics were affected most often in ICS and what are the common architectural security weaknesses in these systems. Our key findings were: (1) Human-Machine Interfaces, SCADA configurations, and PLCs were the most affected components, (2) 62.86% of vulnerability disclosures in ICS had an architectural root cause, (3) the most common architectural weaknesses were “Improper Input Validation”, followed by “Im-proper Neutralization of Input During Web Page Generation” and “Improper Authentication”, and (4) most tactic-related vulnerabilities were related to the tactics “Validate Inputs”, “Authenticate Actors” and “Authorize Actors”.

2019-07-01
Akhtar, T., Gupta, B. B., Yamaguchi, S..  2018.  Malware propagation effects on SCADA system and smart power grid. 2018 IEEE International Conference on Consumer Electronics (ICCE). :1–6.

Critical infrastructures have suffered from different kind of cyber attacks over the years. Many of these attacks are performed using malwares by exploiting the vulnerabilities of these resources. Smart power grid is one of the major victim which suffered from these attacks and its SCADA system are frequently targeted. In this paper we describe our proposed framework to analyze smart power grid, while its SCADA system is under attack by malware. Malware propagation and its effects on SCADA system is the focal point of our analysis. OMNeT++ simulator and openDSS is used for developing and analyzing the simulated smart power grid environment.

Urias, V. E., Stout, M. S. William, Leeuwen, B. V..  2018.  On the Feasibility of Generating Deception Environments for Industrial Control Systems. 2018 IEEE International Symposium on Technologies for Homeland Security (HST). :1–6.

The cyber threat landscape is a constantly morphing surface; the need for cyber defenders to develop and create proactive threat intelligence is on the rise, especially on critical infrastructure environments. It is commonly voiced that Supervisory Control and Data Acquisition (SCADA) systems and Industrial Control Systems (ICS) are vulnerable to the same classes of threats as other networked computer systems. However, cyber defense in operational ICS is difficult, often introducing unacceptable risks of disruption to critical physical processes. This is exacerbated by the notion that hardware used in ICS is often expensive, making full-scale mock-up systems for testing and/or cyber defense impractical. New paradigms in cyber security have focused heavily on using deception to not only protect assets, but also gather insight into adversary motives and tools. Much of the work that we see in today's literature is focused on creating deception environments for traditional IT enterprise networks; however, leveraging our prior work in the domain, we explore the opportunities, challenges and feasibility of doing deception in ICS networks.

Perez, R. Lopez, Adamsky, F., Soua, R., Engel, T..  2018.  Machine Learning for Reliable Network Attack Detection in SCADA Systems. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :633–638.

Critical Infrastructures (CIs) use Supervisory Control And Data Acquisition (SCADA) systems for remote control and monitoring. Sophisticated security measures are needed to address malicious intrusions, which are steadily increasing in number and variety due to the massive spread of connectivity and standardisation of open SCADA protocols. Traditional Intrusion Detection Systems (IDSs) cannot detect attacks that are not already present in their databases. Therefore, in this paper, we assess Machine Learning (ML) for intrusion detection in SCADA systems using a real data set collected from a gas pipeline system and provided by the Mississippi State University (MSU). The contribution of this paper is two-fold: 1) The evaluation of four techniques for missing data estimation and two techniques for data normalization, 2) The performances of Support Vector Machine (SVM), and Random Forest (RF) are assessed in terms of accuracy, precision, recall and F1score for intrusion detection. Two cases are differentiated: binary and categorical classifications. Our experiments reveal that RF detect intrusions effectively, with an F1score of respectively \textbackslashtextgreater 99%.

Zabetian-Hosseini, A., Mehrizi-Sani, A., Liu, C..  2018.  Cyberattack to Cyber-Physical Model of Wind Farm SCADA. IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society. :4929–4934.

In recent years, there has been a significant increase in wind power penetration into the power system. As a result, the behavior of the power system has become more dependent on wind power behavior. Supervisory control and data acquisition (SCADA) systems responsible for monitoring and controlling wind farms often have vulnerabilities that make them susceptible to cyberattacks. These vulnerabilities allow attackers to exploit and intrude in the wind farm SCADA system. In this paper, a cyber-physical system (CPS) model for the information and communication technology (ICT) model of the wind farm SCADA system integrated with SCADA of the power system is proposed. Cybersecurity of this wind farm SCADA system is discussed. Proposed cyberattack scenarios on the system are modeled and the impact of these cyberattacks on the behavior of the power systems on the IEEE 9-bus modified system is investigated. Finally, an anomaly attack detection algorithm is proposed to stop the attack of tripping of all wind farms. Case studies validate the performance of the proposed CPS model of the test system and the attack detection algorithm.

Kolosok, I., Korkina, E., Mahnitko, A., Gavrilovs, A..  2018.  Supporting Cyber-Physical Security of Electric Power System by the State Estimation Technique. 2018 IEEE 59th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON). :1–6.

Security is one of the most important properties of electric power system (EPS). We consider the state estimation (SE) tool as a barrier to the corruption of data on current operating conditions of the EPS. An algorithm for a two-level SE on the basis of SCADA and WAMS measurements is effective in terms of detection of malicious attacks on energy system. The article suggests a methodology to identify cyberattacks on SCADA and WAMS.

Kumar, S., Gaur, N., Kumar, A..  2018.  Developing a Secure Cyber Ecosystem for SCADA Architecture. 2018 Second International Conference on Computing Methodologies and Communication (ICCMC). :559–562.

Advent of Cyber has converted the entire World into a Global village. But, due to vurneabilites in SCADA architecture [1] national assests are more prone to cyber attacks.. Cyber invasions have a catastrophic effect in the minds of the civilian population, in terms of states security system. A robust cyber security is need of the hour to protect the critical information infastructrue & critical infrastructure of a country. Here, in this paper we scrutinize cyber terrorism, vurneabilites in SCADA network systems [1], [2] and concept of cyber resilience to combat cyber attacks.