Relevant bibliographies by topics / IDS SCADA

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'IDS SCADA'

Author: Grafiati
Published: 5 June 2025
Last updated: 11 July 2025

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Journal articles on the topic "IDS SCADA"

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Syamsul Arifin, M. Agus, Susanto Susanto, Deris Stiawan, Mohd Yazid Idris, and Rahmat Budiarto. "The trends of supervisory control and data acquisition security challenges in heterogeneous networks." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 2 (2021): 874. http://dx.doi.org/10.11591/ijeecs.v22.i2.pp874-883.

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<p>Supervisory control and data acquisition (SCADA) has an important role in communication between devices in strategic industries such as power plant grid/network. Besides, the SCADA system is now open to any external heterogeneous networks to facilitate monitoring of industrial equipment, but this causes a new vulnerability in the SCADA network system. Any disruption on the SCADA system will give rise to a dangerous impact on industrial devices. Therefore, deep research and development of reliable intrusion detection system (IDS) for SCADA system/network is required. Via a thorough literature review, this paper firstly discusses current security issues of SCADA system and look closely benchmark dataset and SCADA security holes, followed by SCADA traffic anomaly recognition using artificial intelligence techniques and visual traffic monitoring system. Then, touches on the encryption technique suitable for the SCADA network. In the end, this paper gives the trend of SCADA IDS in the future and provides a proposed model to generate a reliable IDS, this model is proposed based on the investigation of previous researches. This paper focuses on SCADA systems that use IEC 60870-5-104 (IEC 104) protocol and distributed network protocol version 3 (DNP3) protocol as many SCADA systems use these two protocols.</p>
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Arifin, M. Agus Syamsul, Susanto Susanto, Deris Stiawan, Mohd Yazid Idris, and Rahmat Budiarto. "The trends of supervisory control and data acquisition security challenges in heterogeneous networks." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 2 (2021): 874–83. https://doi.org/10.11591/ijeecs.v22.i2.pp874-883.

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Supervisory control and data acquisition (SCADA) has an important role in communication between devices in strategic industries such as power plant grid/network. Besides, the SCADA system is now open to any external heterogeneous networks to facilitate monitoring of industrial equipment, but this causes a new vulnerability in the SCADA network system. Any disruption on the SCADA system will give rise to a dangerous impact on industrial devices. Therefore, deep research and development of reliable intrusion detection system (IDS) for SCADA system/network is required. Via a thorough literature review, this paper firstly discusses current security issues of SCADA system and look closely benchmark dataset and SCADA security holes, followed by SCADA traffic anomaly recognition using artificial intelligence techniques and visual traffic monitoring system. Then, touches on the encryption technique suitable for the SCADA network. In the end, this paper gives the trend of SCADA IDS in the future and provides a proposed model to generate a reliable IDS, this model is proposed based on the investigation of previous researches. This paper focuses on SCADA systems that use IEC 60870-5-104 (IEC 104) protocol and distributed network protocol version 3 (DNP3) Protocol as many SCADA systems use these two protocols.
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Cruz, Tiago, Jorge Proença, Paulo Simões, et al. "A Distributed IDS for Industrial Control Systems." International Journal of Cyber Warfare and Terrorism 4, no. 2 (2014): 1–22. http://dx.doi.org/10.4018/ijcwt.2014040101.

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Cyber-threats are one of the most significant problems faced by modern Industrial Control Systems (ICS), such as SCADA (Supervisory Control and Data Acquisition) systems, as the vulnerabilities of ICS technology become serious threats that can ultimately compromise human lives. This situation demands a domain-specific approach to cyber threat detection within ICS, which is one of the most important contributions of the CockpitCI FP7 project (http://CockpitCI.eu). Specifically, this paper will present the CockpitCI distributed Intrusion Detection System (IDS) for ICS, which provides its core cyber-detection and analysis capabilities, also including a description of its components, in terms of role, operation, integration, and remote management. Moreover, it will also introduce and describe new domain-specific solutions for ICS security such as the SCADA Honeypot and the Shadow Security Unit, which are part of the CockcpitCI IDS framework.
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D'Aquino, Anderson Mussel, Luiz Fernando Rust da Costa Carmo, Luci Pirmez, and Claudio Miceli de Farias. "IBEMCS: IDS BASEADO EM EVENTOS MULTI-CONTEXTO PARA SCADA / IBEMCS: EVENT BASED IDS MULTI-CONTEXT FOR SCADA." Brazilian Journal of Development 7, no. 1 (2021): 3975–92. http://dx.doi.org/10.34117/bjdv7n1-269.

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Krishnan Sadhasivan, Dhanalakshmi, and Kannapiran Balasubramanian. "A Fusion of Multiagent Functionalities for Effective Intrusion Detection System." Security and Communication Networks 2017 (2017): 1–15. http://dx.doi.org/10.1155/2017/6216078.

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Provision of high security is one of the active research areas in the network applications. The failure in the centralized system based on the attacks provides less protection. Besides, the lack of update of new attacks arrival leads to the minimum accuracy of detection. The major focus of this paper is to improve the detection performance through the adaptive update of attacking information to the database. We propose an Adaptive Rule-Based Multiagent Intrusion Detection System (ARMA-IDS) to detect the anomalies in the real-time datasets such as KDD and SCADA. Besides, the feedback loop provides the necessary update of attacks in the database that leads to the improvement in the detection accuracy. The combination of the rules and responsibilities for multiagents effectively detects the anomaly behavior, misuse of response, or relay reports of gas/water pipeline data in KDD and SCADA, respectively. The comparative analysis of the proposed ARMA-IDS with the various existing path mining methods, namely, random forest, JRip, a combination of AdaBoost/JRip, and common path mining on the SCADA dataset conveys that the effectiveness of the proposed ARMA-IDS in the real-time fault monitoring. Moreover, the proposed ARMA-IDS offers the higher detection rate in the SCADA and KDD cup 1999 datasets.
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Balla, Asaad, Mohamed Hadi Habaebi, Elfatih A. A. Elsheikh, Md Rafiqul Islam, and F. M. Suliman. "The Effect of Dataset Imbalance on the Performance of SCADA Intrusion Detection Systems." Sensors 23, no. 2 (2023): 758. http://dx.doi.org/10.3390/s23020758.

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Integrating IoT devices in SCADA systems has provided efficient and improved data collection and transmission technologies. This enhancement comes with significant security challenges, exposing traditionally isolated systems to the public internet. Effective and highly reliable security devices, such as intrusion detection system (IDSs) and intrusion prevention systems (IPS), are critical. Countless studies used deep learning algorithms to design an efficient IDS; however, the fundamental issue of imbalanced datasets was not fully addressed. In our research, we examined the impact of data imbalance on developing an effective SCADA-based IDS. To investigate the impact of various data balancing techniques, we chose two unbalanced datasets, the Morris power dataset, and CICIDS2017 dataset, including random sampling, one-sided selection (OSS), near-miss, SMOTE, and ADASYN. For binary classification, convolutional neural networks were coupled with long short-term memory (CNN-LSTM). The system’s effectiveness was determined by the confusion matrix, which includes evaluation metrics, such as accuracy, precision, detection rate, and F1-score. Four experiments on the two datasets demonstrate the impact of the data imbalance. This research aims to help security researchers in understanding imbalanced datasets and their impact on DL SCADA-IDS.
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Khadidos, Alaa O., Hariprasath Manoharan, Shitharth Selvarajan, Adil O. Khadidos, Khaled H. Alyoubi, and Ayman Yafoz. "A Classy Multifacet Clustering and Fused Optimization Based Classification Methodologies for SCADA Security." Energies 15, no. 10 (2022): 3624. http://dx.doi.org/10.3390/en15103624.

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Detecting intrusions from the supervisory control and data acquisition (SCADA) systems is one of the most essential and challenging processes in recent times. Most of the conventional works aim to develop an efficient intrusion detection system (IDS) framework for increasing the security of SCADA against networking attacks. Nonetheless, it faces the problems of complexity in classification, requiring more time for training and testing, as well as increased misprediction results and error outputs. Hence, this research work intends to develop a novel IDS framework by implementing a combination of methodologies, such as clustering, optimization, and classification. The most popular and extensively utilized SCADA attacking datasets are taken for this system’s proposed IDS framework implementation and validation. The main contribution of this work is to accurately detect the intrusions from the given SCADA datasets with minimized computational operations and increased accuracy of classification. Additionally the proposed work aims to develop a simple and efficient classification technique for improving the security of SCADA systems. Initially, the dataset preprocessing and clustering processes were performed using the multifacet data clustering model (MDCM) in order to simplify the classification process. Then, the hybrid gradient descent spider monkey optimization (GDSMO) mechanism is implemented for selecting the optimal parameters from the clustered datasets, based on the global best solution. The main purpose of using the optimization methodology is to train the classifier with the optimized features to increase accuracy and reduce processing time. Moreover, the deep sequential long short term memory (DS-LSTM) is employed to identify the intrusions from the clustered datasets with efficient data model training. Finally, the proposed optimization-based classification methodology’s performance and results are validated and compared using various evaluation metrics.
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Sangeetha K., Shitharth S., and Gouse Baig Mohammed. "Enhanced SCADA IDS Security by Using MSOM Hybrid Unsupervised Algorithm." International Journal of Web-Based Learning and Teaching Technologies 17, no. 2 (2022): 1–9. http://dx.doi.org/10.4018/ijwltt.20220301.oa2.

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In Self-Organizing Maps (SOM) are unsupervised neural networks that cluster high dimensional data and transform complex inputs into easily understandable inputs. To find the closest distance and weight factor, it maps high dimensional input space to low dimensional input space. The Closest node to data point is denoted as a neuron. It classifies the input data based on these neurons. The reduction of dimensionality and grid clustering using neurons makes to observe similarities between the data. In our proposed Mutated Self Organizing Maps (MSOM) approach, we have two intentions. One is to eliminate the learning rate and to decrease the neighborhood size and the next one is to find out the outliers in the network. The first one is by calculating the median distance (MD) between each node with its neighbor nodes. Then those median values are compared with one another. In case, if any of the MD values significantly varies from the rest then it is declared as anomaly nodes. In the second phase, we find out the quantization error (QE) in each instance from the cluster center.
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Altaha, Mustafa, and Sugwon Hong. "Anomaly Detection for SCADA System Security Based on Unsupervised Learning and Function Codes Analysis in the DNP3 Protocol." Electronics 11, no. 14 (2022): 2184. http://dx.doi.org/10.3390/electronics11142184.

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An Intrusion Detection System (IDS) is a tool used primarily for security monitoring, which is one of the security strategies for Supervisory Control and Data Acquisition (SCADA) systems. Distributed Network Protocol version 3 (DNP3) is the predominant SCADA protocol in the energy sector. In this paper, we have developed an effective and flexible IDS for DNP3 networks, observing that most critical operations in DNP3 systems are utilized based on the function codes in DNP3 application messages, and that exploitation of those function codes enables attackers to manipulate the system operation. Our proposed anomaly-detection method deals with possible attacks that can bypass any rule-based deep packet inspection once attackers take over servers in the system. First, we generated datasets that reflected DNP3 traffic characteristics observed in real-world power grid substations for a reasonably long time. Next, we extracted input features that consisted of the occurrences of function codes per TCP connection, along with TCP characteristics. We then used an unsupervised deep learning model (Autoencoder) to learn the normal behavior of DNP3 traffic based on function code patterns. We called our approach FC-AE-IDS (Function Code Autoencoder IDS). The evaluation of the proposed method was carried out on three different datasets, to prove its accuracy and effectiveness. To evaluate the effectiveness of our proposed method, we performed various experiments that resulted in more than 95% detection accuracy for all considered attack scenarios that are mentioned in this study. We compared our approach to an IDS that is based on traditional features, to show the effectiveness of our approach.
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Nguyen, Van Xuan. "DETECTING ATTACKS ON SCADA SYSTEMS BASED ON MLP NEURAL NETWORK AND CONTEXT OF DATA." Journal of Science and Technique 15, no. 2 (2020): 98–110. http://dx.doi.org/10.56651/lqdtu.jst.v15.n02.146.

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In this paper, we propose an IDS-SCADA model, which is capable of detecting attacks on SCADA systems with high accuracy. The proposed model is based on two hidden layers MLP neural network, whose number of neurons in the hidden layers is optimally utilizing a genetic algorithm. The distinction of the proposed method is that the context of the data is incorporated into the MLP neural network to accurately identify the attacks. To create the context, the original dataset is reorganized as context vectors containing some consecutive packets before feeding into the input of the MLP. The experimental results show that the proposed system outperforms the conventional in terms of accuracy.
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Dissertations / Theses on the topic "IDS SCADA"

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Fahlström, Albin, and Victor Henriksson. "Intrångsdetektering i processnätverk." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-39881.

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The threat against industrial networks have increased, which raises the demands on the industries cybersecurity. The industrial networks are not constructed with cybersecurity in mind, which makes these systems vulnerable to attacks. Even if the networks outer protection is deemed sufficient, the system may still be infected. This risk demands an intrusion detection system (IDS) that can identify infected components. An IDS scans all traffic of a point in the network and looks for traffic matching its detections parameters, if a match is made the IDS will send an alarm to the administrators. It can also analyze the network traffic using a behavior based method which means that the IDS will alert administrators if network activity deviates from the normal traffic flow. It is of vital essence that the IDS do not impair with the system, an outage of the industrial process can have a high cost for the industry. This report aims to put forward plans for the implementation of an IDS in one of Mälarenergi AB’s industrial networks, this will be made using the Bro and Snort intrusion detection systems.<br>Hoten mot industrinätverken har blivit större vilket har ställt högre krav på industriernas cybersäkerhet. Industrinätverk är ofta inte konstruerade med cybersäkerhet i åtanke, vilket har gjort dessa system sårbara mot attacker. Även om nätverkets yttre skydd anses gott går det inte att vara säker på att ett industrinätverk förblir osmittat. Detta ställer krav på någon form av intrångsdetekteringssystem (IDS) som kan upptäcka infekterad utrustning och suspekt datatrafik i nätverket. En IDS skannar alla paket vid en viss punkt i nätverket, om IDS:en upptäcker något paket som matchar med dess signatur kommer den att larma en administratör. IDS:en kan även använda beteendeanalys där den larmar om nätverksaktiviteten avviker från det normala. Det är mycket viktigt att en IDS inte orsakar avbrott i industriprocessen, om en process stannar kan det innebära stora kostnader för industrin. Denna rapport syftar till att lämna ett lösningsförslag på en IDS-implementation till ett av Mälarenergi AB: s processnätverk, lösningen konstruerades med hjälp av IDS:erna Bro och Snort.<br><p>Vissa bilder i den elektroniska rapporten har tagits bort av upphovrättsliga skäl. Författarna har bedömt att rapporten är förståelig även utan dessa bilder. </p>
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Kuchař, Karel. "Vhodná strategie pro detekci bezpečnostních incidentů v průmyslových sítích." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2020. http://www.nusl.cz/ntk/nusl-412978.

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This diploma thesis is focused on problematics of the industrial networks and offered security by the industrial protocols. The goal of this thesis is to create specific methods for detection of security incidents. This thesis is mainly focused on protocols Modbus/TCP and DNP3. In the theoretical part, the industrial protocols are described, there are defined vectors of attacks and is described security of each protocol. The practical part is focused on the description and simulation of security incidents. Based on the data gathered from the simulations, there are identified threats by the introduced detection methods. These methods are using for detecting the security incident an abnormality in the network traffic by created formulas or machine learning. Designed methods are implemented to IDS (Intrusion Detection System) of the system Zeek. With the designed methods, it is possible to detect selected security incidents in the destination workstation.
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Ševčík, Michal. "Návrh monitoringu kritické komunikační infrastruktury pro energetickou společnost." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2018. http://www.nusl.cz/ntk/nusl-378335.

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Diploma thesis deals with monitoring critical infrastructure, critical information infrastructure and network monitoring in energetic industry. The goal is to create analytical environment for processing logs from the network, to map the most critical segments of the network and implementation of monitoring and network devices, that increase security and mitigate risks of security events or security incidents
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Hansen, Sinclair D. "An intrusion detection system for supervisory control and data acquisition systems." Thesis, Queensland University of Technology, 2008. https://eprints.qut.edu.au/16636/1/Sinclair_Hansen_Thesis.pdf.

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Despite increased awareness of threats against Critical Infrastructure (CI), securing of Supervisory Control and Data Acquisition (SCADA) systems remains incomplete. The majority of research focuses on preventative measures such as improving communication protocols and implementing security policies. New attempts are being made to use commercial Intrusion Detection System (IDS) software to protect SCADA systems. These have limited effectiveness because the ability to detect specific threats requires the context of the SCADA system. SCADA context is defined as any information that can be used to characterise the current status and function of the SCADA system. In this thesis the standard IDS model will be used with the varying SCADA data sources to provide SCADA context to a signature and anomaly detection engine. A novel addition to enhance the IDS model will be to use the SCADA data sources to simulate the remote SCADA site. The data resulting from the simulation is used by the IDS to make behavioural comparison between the real and simulated SCADA site. To evaluate the enhanced IDS model the specific context of a water and wastewater system is used to develop a prototype. Using this context it was found that the inflow between sites has similar diurnal characteristic to network traffic. This introduced the idea of using inflow data to detect abnormal behaviour for a remote wastewater site. Several experiments are proposed to validate the prototype using data from a real SCADA site. Initial results show good promise for detecting abnormal behaviour and specific threats against water and wastewater SCADA systems.
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Hansen, Sinclair D. "An intrusion detection system for supervisory control and data acquisition systems." Queensland University of Technology, 2008. http://eprints.qut.edu.au/16636/.

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Despite increased awareness of threats against Critical Infrastructure (CI), securing of Supervisory Control and Data Acquisition (SCADA) systems remains incomplete. The majority of research focuses on preventative measures such as improving communication protocols and implementing security policies. New attempts are being made to use commercial Intrusion Detection System (IDS) software to protect SCADA systems. These have limited effectiveness because the ability to detect specific threats requires the context of the SCADA system. SCADA context is defined as any information that can be used to characterise the current status and function of the SCADA system. In this thesis the standard IDS model will be used with the varying SCADA data sources to provide SCADA context to a signature and anomaly detection engine. A novel addition to enhance the IDS model will be to use the SCADA data sources to simulate the remote SCADA site. The data resulting from the simulation is used by the IDS to make behavioural comparison between the real and simulated SCADA site. To evaluate the enhanced IDS model the specific context of a water and wastewater system is used to develop a prototype. Using this context it was found that the inflow between sites has similar diurnal characteristic to network traffic. This introduced the idea of using inflow data to detect abnormal behaviour for a remote wastewater site. Several experiments are proposed to validate the prototype using data from a real SCADA site. Initial results show good promise for detecting abnormal behaviour and specific threats against water and wastewater SCADA systems.
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Mareček, Matěj. "IDE for SCADA Development at CERN." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2016. http://www.nusl.cz/ntk/nusl-255482.

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Cílem této magisterské práce je navrhnout a implementovat IDE (integrované vývojové prostředí), které zvýší efektivitu a bezpečnost vývoje pro SIMATIC WinCC Open Architecture. Tato práce je založena na výzkumu provedeném týmem z Technické univerzity v Eindhovenu a splňuje požadavky pocházející ze SCD sekce v CERN (Evropské organizace pro jaderný výzkum). Vyvinuté IDE je postaveno na platformě Eclipse, přičemž pro syntaktickou analýzu, linkování a sémantickou analýzu kódu používá Xtext framework. IDE nabízí také podporu pro nově vytvořený programovací jazyk, který umožňuje programátorům jednoduše nadefinovat šablonu pro konfigurační soubory používané WinCC OA. Interpret tohoto nového jazyka je schopen provést syntaktickou analýzu šablony a konfiguračního souboru a rozhodnout, zdali konfigurační soubor odpovídá šabloně. Praktickým výstupem této práce je integrované vývojové prostředí, které podporuje vývoj WinCC OA aplikací v CERN a periodicky provádí analýzu kódu těchto aplikací napsaného v jazyce Control script.
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Váňa, Martin. "Kybernetické prostředí pro systémy typu ICS/SCADA." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2019. http://www.nusl.cz/ntk/nusl-400894.

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The thesis explores the problematics of cyber environment for the ICS/SCADA systems. First, shorter section is mainly focused on general introduction into the ICS/SCADA systems and their inner workings. Communication model of a general SCADA system and its foundational elements are explained. It is mainly theoretical passage and it serves as an introduction. It is necessary for understanding the second part which is mainly practical. The appropriate system is chosen as a first thing in the practical part of the thesis for the implementation of the whole project. There are defined criteria on which the system itself is implemented. Following that the system itself is implemented under a framework called openMUC and it is tested with help of the simulators according to the objective of the thesis.
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Albinsson, Felix, and Jesper Riedl. "HONEYPOT – To bee or not to bee: A study of attacks on ICS/SCADA systems." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-54563.

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In the past, industrial control systems (ICS) and supervisory control and data acquisition (SCADA) systems were planned to run as isolated networks, and not interconnect with other networks e.g., the internet or other parts of a corporate’s network. Because of the isolation, no cybersecurity mechanism was required. In the modern society, ICS/SCADA systems has evolved to communicate over public IP networks and has been incorporated in a company’s intranet or directly to the internet. This integration opens up for threats that were not envisioned at the time when the system was created. When ICS/SCADA systems get exposed to the internet, there is a risk that vulnerabilities in the systems get exploited by a malicious force. This can lead to data loss, destruction of data and devices, damage to infrastructure, financial losses for the company, and even loss of human life could occur. To mitigate and prevent attacks it is crucial to understand the attacks and the behaviour of the attacker. One way to achieve this is setting up a system that mimics the real system. This fake system is separated from the production network and closely monitored. The data collected can be analysed and used to gain knowledge about the attacks. This thesis will present a possible way to study attacks on an ICS/SCADA system using a honeypot designed for this purpose. To do this, a suitable honeypot had to be found that could collect relevant data regarding what kind of attacks that may be used against an ICS/SCADA system. This was achieved by experimenting with different set ups, and the collected data was analysed. This led to the use of T-pot as the chosen honeypot and the collected data showed that a lot of the traffic were directed towards the ICS/SCADA communication protocols Modbus and s7comm. To secure an ICS/SCADA system, it is important to gain knowledge about attacks and attack vectors. A honeypot can be a useful tool that provide information regarding attacks and attackers and can be a help in setting up a defence-in-depth strategy to improve the security in an ICS/SCADA network.
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Xu, Hao. "WINCC SCADA system via profibus & OPC." Thesis, Xu, Hao (2013) WINCC SCADA system via profibus & OPC. Other thesis, Murdoch University, 2013. https://researchrepository.murdoch.edu.au/id/eprint/21651/.

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Over 1500 hours' effort were put into this intensive project with 6 weeks prior to the commencing date of the project to meet the objectives and requirements of the project. During this project, all the available devices, instruments including their configuration software were properly configured with all the expected features fully functioning. This thesis report summaries most of the work done with a reasonably detailed level to support future students with a comprehensive background to develop the project aspects in the future. A comprehensive SCADA system was designed and implemented using the configured devices and the control modules in the laboratory. The network structure of the control system was relatively large, but indeed demonstrated the capability of the automation system. Profibus communication networks in the laboratory were carefully designed and fully set up with proper labels, which would then be used as an education tool to gain the experience of industrial communication by the students. Over 500 pages of configuration manuals of devices and configuration software were created as a large part of the focus of this project. The configuration manuals contain a huge range of information which covers more than what students need during their study. Those manuals are expected to guide students for their projects and troubleshooting.
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Myers, David. "Detecting cyber attacks on industrial control systems using process mining." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/130799/1/David_Myers_Thesis.pdf.

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Industrial control systems conduct processes which are core to our lives, from the generation, transmission, and distribution of power, to the treatment and supply of water. These industrial control systems are moving from dedicated, serial-based communications to switched and routed corporate networks to facilitate the monitoring and management of an industrial processes. However, this connection to corporate networks can expose industrial control systems to the Internet, placing them at risk of cyber-attack. In this study, we develop and evaluate a process-mining based anomaly detection system to generate process models of, and detect cyber-attacks on, industrial control system processes and devices.
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Books on the topic "IDS SCADA"

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author, Singer Bryan L., Shbeeb Aaron author, Hilt Stephen author, and Wilhoit Kyle author, eds. Hacking exposed industrial control systems: ICS and SCADA security secrets & solutions. McGraw-Hill Education, 2017.

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Jones, Kevin, Helge Janicke, and Thomas Brandstetter. 4th International Symposium for ICS and SCADA Cyber Security Research 2016. BCS Learning & Development Limited, 2016.

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Singer, Bryan, Clint Bodungen, Aaron Shbeeb, Kyle Wilhoit, and Stephen Hilt. Hacking Exposed Industrial Control Systems: ICS and Scada Security Secrets and Solutions. McGraw-Hill Education, 2016.

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Book chapters on the topic "IDS SCADA"

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Bayou, Lyes, David Espes, Nora Cuppens-Boulahia, and Frédéric Cuppens. "wIDS: A Multilayer IDS for Wireless-Based SCADA Systems." In Information Systems Security. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-72598-7_24.

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Shitharth, S., N. Satheesh, B. Praveen Kumar, and K. Sangeetha. "IDS Detection Based on Optimization Based on WI-CS and GNN Algorithm in SCADA Network." In Architectural Wireless Networks Solutions and Security Issues. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0386-0_14.

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Strohmier, Hala, Aaryan R. Londhe, Chris A. Clark, Ronit Pawar, and Brian Kram. "Exploring ICS/SCADA Network Vulnerabilities." In HCI for Cybersecurity, Privacy and Trust. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-61382-1_14.

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Ali, Saqib, Taiseera Al Balushi, Zia Nadir, and Omar Khadeer Hussain. "ICS/SCADA System Security for CPS." In Studies in Computational Intelligence. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75880-0_5.

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Gaiceanu, Marian, Marilena Stanculescu, Paul Cristian Andrei, Vasile Solcanu, Theodora Gaiceanu, and Horia Andrei. "Intrusion Detection on ICS and SCADA Networks." In Recent Developments on Industrial Control Systems Resilience. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31328-9_10.

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Kim, Byoung-Koo, Dong-Ho Kang, Jung-Chan Na, and Tai-Myoung Chung. "Detecting Abnormal Behavior in SCADA Networks Using Normal Traffic Pattern Learning." In Computer Science and its Applications. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-45402-2_18.

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Chaudhry, Junaid, Uvais Qidwai, and Mahdi H. Miraz. "Securing Big Data from Eavesdropping Attacks in SCADA/ICS Network Data Streams through Impulsive Statistical Fingerprinting." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23943-5_6.

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Radaković, Nataša, and Ivana Šenk. "Deep Autoencoder Based Leakage Detection in Water Distribution SCADA Systems." In Proceedings on 18th International Conference on Industrial Systems – IS’20. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97947-8_47.

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Guo, Youqiang, Zijun Zhang, and Xuezhu Pei. "A Research on Instability of Small Flow in SCADA and an Optimizing Design for Control." In Computational Science and Its Applications – ICCSA 2009. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02457-3_55.

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Maglaras, Leandros, Helge Janicke, Jianmin Jiang, and Andrew Crampton. "Novel Intrusion Detection Mechanism with Low Overhead for SCADA Systems." In Securing the Internet of Things. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-5225-9866-4.ch017.

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SCADA (Supervisory Control and Data Acquisition) systems are a critical part of modern national critical infrastructure (CI) systems. Due to the rapid increase of sophisticated cyber threats with exponentially destructive effects, intrusion detection systems (IDS) must systematically evolve. Specific intrusion detection systems that reassure both high accuracy, low rate of false alarms and decreased overhead on the network traffic must be designed for SCADA systems. In this book chapter we present a novel IDS, namely K-OCSVM, that combines both the capability of detecting novel attacks with high accuracy, due to its core One-Class Support Vector Machine (OCSVM) classification mechanism and the ability to effectively distinguish real alarms from possible attacks under different circumstances, due to its internal recursive k-means clustering algorithm. The effectiveness of the proposed method is evaluated through extensive simulations that are conducted using realistic datasets extracted from small and medium sized HTB SCADA testbeds.
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Conference papers on the topic "IDS SCADA"

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Rubin, Benny, Ali Tekeoglu, and Christopher Rouff. "Autonomic Passive IT-OT Device Classification in ICS/SCADA Networks." In 2024 IEEE International Conference on Cyber Security and Resilience (CSR). IEEE, 2024. http://dx.doi.org/10.1109/csr61664.2024.10679418.

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R, Senthilprabha, Dharini V, Jyothika G, and Shophiya K. "Performance Measure of IDS in the SCADA Systems." In Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India. EAI, 2021. http://dx.doi.org/10.4108/eai.7-12-2021.2314694.

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D’Aquino, Anderson Mussel, Luiz Fernando Rust da Costa Carmo, Luci Pirmez, and Claudio Miceli. "IBEMCS: IDS Baseado em Eventos Multi-Contexto para SCADA." In Simpósio Brasileiro de Segurança da Informação e de Sistemas Computacionais. Sociedade Brasileira de Computação - SBC, 2016. http://dx.doi.org/10.5753/sbseg.2016.19302.

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Atualmente os mecanismos de segurança utilizados para detecção de intrusão em ambientes de automação industrial utilizam dados exclusivos TIC (Tecnologia da Informação e Comunicação) ou TO (Tecnologia da Operação). Este trabalho propõe um IDS (Intrusion Detection System) que integra informações TIC e TO para identificação das cadeias de eventos TIC e TO que ocasionaram a falha no processo industrial. Medições demonstram que o tempo de resposta e a taxa de acerto são linearmente proporcionais ao volume de dados processados permitindo um planejamento prévio da arquitetura ao ambiente de trabalho.
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Verba, Jared, and Michael Milvich. "Idaho National Laboratory Supervisory Control and Data Acquisition Intrusion Detection System (SCADA IDS)." In 2008 IEEE Conference on Technologies for Homeland Security. IEEE, 2008. http://dx.doi.org/10.1109/ths.2008.4534498.

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Chen, Yenan, Linsen Li, Zhaoqian Zhu, and Yue Wu. "Work-in-Progress: Reliability Evaluation of Power SCADA System with Three-Layer IDS." In 2022 International Conference on Compilers, Architecture, and Synthesis for Embedded Systems (CASES). IEEE, 2022. http://dx.doi.org/10.1109/cases55004.2022.00007.

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Vasquez, Gabriel, Rodrigo S. Miani, and Bruno B. Zarpelão. "Flow-Based Intrusion Detection for SCADA networks using Supervised Learning." In Simpósio Brasileiro de Segurança da Informação e de Sistemas Computacionais. Sociedade Brasileira de Computação - SBC, 2017. http://dx.doi.org/10.5753/sbseg.2017.19498.

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Recent attacks on industrial networks have brought the question of their protection, given the importance of the equipment that they control. In this paper, we address the application of Machine Learning (ML) algorithms to build an Intrusion Detection System (IDS) for these networks. As network traffic usually has much less malicious packets than normal ones, intrusion detection problems have class imbalance as a key characteristic, which can be a challenge for ML algorithms. Therefore, we study the performance of nine different ML algorithms in classifying IP flows of an industrial network, analyzing the impact of class imbalance in the results. The algorithms were evaluated taking as main metrics the F1-Score and Averaged Accuracy. Our experiments showed that the three algorithms based on decision trees were superior to the others. Particularly, the Decision Jungle algorithm outperformed all the others.
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Ouyang, Yuankai, Beibei Li, Qinglei Kong, Han Song, and Tao Li. "FS-IDS: A Novel Few-Shot Learning Based Intrusion Detection System for SCADA Networks." In ICC 2021 - IEEE International Conference on Communications. IEEE, 2021. http://dx.doi.org/10.1109/icc42927.2021.9500667.

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Eden, Peter, Andrew Blyth, Pete Burnap, et al. "Forensic Readiness for SCADA/ICS Incident Response." In 4th International Symposium for ICS & SCADA Cyber Security Research 2016. BCS Learning & Development, 2016. http://dx.doi.org/10.14236/ewic/ics2016.16.

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Nicholson, Andrew, Helge Janicke, and Antonio Cau. "Safety and Security Monitoring in ICS/SCADA Systems." In 2nd International Symposium for ICS & SCADA Cyber Security Research 2014. BCS Learning & Development, 2014. http://dx.doi.org/10.14236/ewic/ics-csr2014.9.

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Green, Benjamin, Daniel Prince, Utz Roedig, Jerry Busby, and David Hutchison. "Socio-Technical Security Analysis of Industrial Control Systems (ICS)." In 2nd International Symposium for ICS & SCADA Cyber Security Research 2014. BCS Learning & Development, 2014. http://dx.doi.org/10.14236/ewic/ics-csr2014.2.

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Reports on the topic "IDS SCADA"

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Stouffer, Keith, Joe Falco, and Karen Scarfone. Guide to Industrial Control Systems (ICS) Security : Supervisory Control and Data Acquisition (SCADA) Systems, Distributed Control Systems (DCS), and Other Control System Configurations such as Programmable Logic Controllers (PLC). National Institute of Standards and Technology, 2013. http://dx.doi.org/10.6028/nist.sp.800-82r1.

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Stouffer, Keith, Joe Falco, and Karen Scarfone. Guide to Industrial Control Systems (ICS) Security - Supervisory Control and Data Acquisition (SCADA) systems, Distributed Control Systems (DCS), and other control system configurations such as Programmable Logic Controllers (PLC). National Institute of Standards and Technology, 2011. http://dx.doi.org/10.6028/nist.sp.800.82.

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Stouffer, Keith, Joe Falco, and Karen Scarfone. Guide to Industrial Control Systems (ICS) security : Supervisory Control and Data Acquisition (SCADA) systems, Distributed Control systems (DCS), and other control system configurations such as Programmable Logic Controllers (PLC) : recommendations of the National Institute of Standards and Technology, Computer security. National Institute of Standards and Technology, 2011. http://dx.doi.org/10.6028/nist.sp.800-82.

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Lindig, Sascha, Julien Deckx, Magnus Herz, et al. Technical Key Performance Indicators for Photovoltaic Systems: Challenges and Best Practices. International Energy Agency Photovoltaic Power Systems Programme, 2024. https://doi.org/10.69766/luzi3108.

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Key Performance Indicators (KPIs) are an important set of metrics used to assess various aspects of photovoltaic (PV) systems, including their long-term performance, economic viability and carbon footprint. Technical KPIs support data-driven and informed decision-making when optimizing PV systems and provide a comprehensive overview of how PV systems operate across different conditions and climates. Different KPIs are commonly employed throughout the entire value chain of PV projects and can be categorized into technical, economic and sustainability aspects. In this work, a set of best practices for handling PV system data to reliably calculate relevant KPIs is discussed. While most technical KPIs are generally well-known among asset owners, EPCs, O&amp;M providers and consultants, not all stakeholders in the financing-to-operation chain are equally aware of the nuances and consequences of certain decisions, which are based on how technical KPIs are operationalized, i.e. translated from contracts to how and where raw data are stored, which data cleaning and imputation techniques are used, to how the technical KPIs are calculated and used for subsequent decision-making. In many cases, the decisions made in the development-to-construction phase, will affect the asset for a significant part of its lifetime. For example, the resolution at which data is measured, which data are stored, or whether data back-ups are on-site or in the cloud, can all affect how KPIs are calculated, affect future modifications to contractual clauses, or the need for SCADA upgrades. Hence, this work aims to provide all stakeholders deeper insights and a shared understanding of the most important technical KPIs. The work is divided into three parts, each addressing different aspects of KPIs, data management, and their mapping potential
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