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Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 28 січня 2023

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Статті в журналах з теми "Stealthy attacks on ICS"

1

Mokhtari, Sohrab, Alireza Abbaspour, Kang K. Yen, and Arman Sargolzaei. "A Machine Learning Approach for Anomaly Detection in Industrial Control Systems Based on Measurement Data." Electronics 10, no. 4 (February 8, 2021): 407. http://dx.doi.org/10.3390/electronics10040407.

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Анотація:
Attack detection problems in industrial control systems (ICSs) are commonly known as a network traffic monitoring scheme for detecting abnormal activities. However, a network-based intrusion detection system can be deceived by attackers that imitate the system’s normal activity. In this work, we proposed a novel solution to this problem based on measurement data in the supervisory control and data acquisition (SCADA) system. The proposed approach is called measurement intrusion detection system (MIDS), which enables the system to detect any abnormal activity in the system even if the attacker tries to conceal it in the system’s control layer. A supervised machine learning model is generated to classify normal and abnormal activities in an ICS to evaluate the MIDS performance. A hardware-in-the-loop (HIL) testbed is developed to simulate the power generation units and exploit the attack dataset. In the proposed approach, we applied several machine learning models on the dataset, which show remarkable performances in detecting the dataset’s anomalies, especially stealthy attacks. The results show that the random forest is performing better than other classifier algorithms in detecting anomalies based on measured data in the testbed.
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2

Zhao, Xiaosong, Lei Zhang, Yixin Cao, Kai Jin, and Yupeng Hou. "Anomaly Detection Approach in Industrial Control Systems Based on Measurement Data." Information 13, no. 10 (September 25, 2022): 450. http://dx.doi.org/10.3390/info13100450.

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Анотація:
Anomaly detection problems in industrial control systems (ICSs) are always tackled by a network traffic monitoring scheme. However, traffic-based anomaly detection systems may be deceived by anomalous behaviors that mimic normal system activities and fail to achieve effective anomaly detection. In this work, we propose a novel solution to this problem based on measurement data. The proposed method combines a one-dimensional convolutional neural network (1DCNN) and a bidirectional long short-term memory network (BiLSTM) and uses particle swarm optimization (PSO), which is called PSO-1DCNN-BiLSTM. It enables the system to detect any abnormal activity in the system, even if the attacker tries to conceal it in the system’s control layer. A supervised deep learning model was generated to classify normal and abnormal activities in an ICS to evaluate the method’s performance. This model was trained and validated against the open-source simulated power system dataset from Mississippi State University. In the proposed approach, we applied several deep-learning models to the dataset, which showed remarkable performance in detecting the dataset’s anomalies, especially stealthy attacks. The results show that PSO-1DCNN-BiLSTM performed better than other classifier algorithms in detecting anomalies based on measured data.
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3

Puzankov, Sergey. "Stealthy SS7 Attacks." Journal of ICT Standardization 5, no. 1 (2017): 39–52. http://dx.doi.org/10.13052/jicts2245-800x.512.

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4

Na, Gyujin, Hanbit Lee, and Yongsoon Eun. "A Multiplicative Coordinated Stealthy Attack for Nonlinear Cyber-Physical Systems with Homogeneous Property." Mathematical Problems in Engineering 2019 (August 29, 2019): 1–13. http://dx.doi.org/10.1155/2019/7280474.

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Анотація:
Stealthy attacks to cyber-physical systems (CPS) refer to the ones that avoid attack detection mechanisms augmented to the systems typically in the form of anomaly detectors. Various types of stealthy attacks have been reported in the literature. Among the attacks with stealthy property, a recently reported multiplicative coordinated attack is particularly dangerous in that it corrupts sensor and actuator data in a coordinated manner, and it does not require precise system knowledge in order to be stealthy. It must be noted that most of these attacks are applicable to CPS, the physical counterparts of which are of linear dynamics. This could be a limitation since most of the physical dynamic systems that are encountered from CPS perspective are of nonlinear nature. In this work, we present a version of multiplicative coordinated stealthy attack for a class of CPS, the physical counterpart of which possesses nonlinear dynamics. Specifically, for the physical systems with homogeneous property, the attack is constructed and the effect is analyzed. Various simulations are carried out to illustrate the effect of the attack.
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5

SHINOHARA, Takumi, and Toru NAMERIKAWA. "Perfect Stealthy Attacks in Cyber-physical Systems." Transactions of the Society of Instrument and Control Engineers 54, no. 3 (2018): 309–19. http://dx.doi.org/10.9746/sicetr.54.309.

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6

Degue, Kwassi Holali, Jerome Le Ny, and Denis Efimov. "Stealthy attacks and attack-resilient interval observers." Automatica 146 (December 2022): 110558. http://dx.doi.org/10.1016/j.automatica.2022.110558.

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Wang, Zhenqian, and Yongqiang Wang. "Pulse-Coupled Oscillators Resilient to Stealthy Attacks." IEEE Transactions on Signal Processing 66, no. 12 (June 1, 2018): 3086–99. http://dx.doi.org/10.1109/tsp.2018.2824285.

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Li, Xuerong, Ping Zhang, and Hongli Dong. "Robust Stealthy Covert Attacks on Cyber-Physical Systems." IFAC-PapersOnLine 55, no. 6 (2022): 520–25. http://dx.doi.org/10.1016/j.ifacol.2022.07.181.

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Rubinstein, Benjamin I. P., Blaine Nelson, Ling Huang, Anthony D. Joseph, Shing-hon Lau, Satish Rao, Nina Taft, and J. D. Tygar. "Stealthy poisoning attacks on PCA-based anomaly detectors." ACM SIGMETRICS Performance Evaluation Review 37, no. 2 (October 16, 2009): 73–74. http://dx.doi.org/10.1145/1639562.1639592.

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Dash, Pritam, Mehdi Karimibiuki, and Karthik Pattabiraman. "Stealthy Attacks against Robotic Vehicles Protected by Control-based Intrusion Detection Techniques." Digital Threats: Research and Practice 2, no. 1 (March 2021): 1–25. http://dx.doi.org/10.1145/3419474.

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Анотація:
Robotic vehicles (RV) are increasing in adoption in many industrial sectors. RVs use auto-pilot software for perception and navigation and rely on sensors and actuators for operating autonomously in the physical world. Control algorithms have been used in RVs to minimize the effects of noisy sensors, prevent faulty actuator output, and, recently, to detect attacks against RVs. In this article, we demonstrate the vulnerabilities in control-based intrusion detection techniques and propose three kinds of stealthy attacks that evade detection and disrupt RV missions. We also propose automated algorithms for performing the attacks without requiring the attacker to expend significant effort or to know specific details of the RV, thus making the attacks applicable to a wide range of RVs. We demonstrate the attacks on eight RV systems including three real vehicles in the presence of an Intrusion Detection System using control-based techniques to monitor RV’s runtime behavior and detect attacks. We find that the control-based techniques are incapable of detecting our stealthy attacks and that the attacks can have significant adverse impact on the RV’s mission (e.g., deviate it significantly from its target, or cause it to crash).
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Більше джерел

Дисертації з теми "Stealthy attacks on ICS"

1

Czarlinska, Aleksandra. "Stealthy attacks and defense strategies in competing sensor networks." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2946.

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2

Flamholz, David B. "Baiting for defense against stealthy attacks on cyber-physical systems." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/121858.

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Анотація:
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 63-64).
The goal of this thesis is to develop a defense methodology for a cyber-physical system (CPS) by which an attempted stealthy cyber-attack is detected in near real time. Improvements in networked communication have enabled vast and complex dynamic control systems to exploit networked control schemes to seamlessly integrate parts and processes. These cyber-physical systems exhibit a level of flexibility that was previously unavailable but also introduce communication channels that are vulnerable to outside interference and malicious intervention. This thesis considers the effects of a type of stealthy attack on a class of CPS that can be modeled as linear time-invariant systems. The effects of this attack are studied from both the perspective of the attacker as well as the defender. A previously developed method for conducting stealthy attacks is introduced and analyzed.
This method consists of injecting malicious actuation signals into the control input of a CPS and then designing a sensor attack to conceal the effect of the actuator attack. The result is an attack that cannot be detected upon inspection of the Kalman filter residual. Successful implementation of this attack is shown to require the attacker to attain perfect model knowledge in order for the attack to be stealthy. Based on the execution of past attacks on CPS, this thesis proposes an attacker who starts their attack by "fishing" for critical and confidential system information such as the model parameters. A method is then proposed in which the defender attempts to feed the attacker a slightly falsified model, baiting the fishing attacker with data that will make an attack detectable. Because the attacker's model is no longer correct, their attack design will induce a mean-shift in the Kalman filter residual, breaking the stealthiness of the original attack formula.
It is then shown that the defender can not only detect this faulty attack, but use observations of the Kalman filter residual to regain more accurate state estimates, mitigating the effect of the attack.
by David B. Flamholz.
S.M.
S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering
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3

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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Анотація:
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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4

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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Анотація:
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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5

Amini, Elham [Verfasser], Christian [Akademischer Betreuer] Boit, Bernd [Akademischer Betreuer] Szyszka, Christian [Gutachter] Boit, Bernd [Gutachter] Szyszka, Jean-Pierre [Gutachter] Seifert, and Navid [Gutachter] Asadi. "A structure for protection of security-sensitive ICs against attacks through silicon backside / Elham Amini ; Gutachter: Christian Boit, Bernd Szyszka, Jean-Pierre Seifert, Navid Asadi ; Christian Boit, Bernd Szyszka." Berlin : Technische Universität Berlin, 2021. http://d-nb.info/1238140831/34.

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6

黃啟彥. "On Study of Stealthy Attacks in a Process Control System with Model-based Anomaly Detection Protection." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/68172228210520738824.

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Анотація:
碩士
國立交通大學
電控工程研究所
98
Process control systems (PCS) are widely used in modern infrastructures and industrial plants for stabilizing safety-critical processes. Any disruption in such systems may cause serious human injuries and environmental disasters. In 2008, Lin et al.~proposed a model-based anomaly detection module (abbreviated to mADM) to assure the security and stability of a well-studied Tennessee-Eastman process control system (TE-PCS). By taking advantages of cumulating the differences between real and simulated signals, mADM was able to detect an attack that compromises one or more sensors to crash the system. To evaluate the robustness of mADM, we study the stealthy attacks launched by an insider who may (1) know the detection and response strategies of mADM or (2) adjust the parameters of mADM so that these stealthy attacks may successfully attack the system without being detected by mADM. After analyzing mADM, we prove that a general stealthy attack signal can be represented by three types of curves, convex curve (cv), slope (sl), and concave curve (cc), depending on the cumulative differences of signals. By conducting a series of experiments on TE-PCS, we can identify the weakest sensor and the most effective way to stealthily attack this sensor. We also show that, if an insider cannot adjust the parameter settings and the parameters are well configured, he may not be able to crash the system. In the case that the insider obtains the permission to adjust the parameter settings, mADM should self-check whether the settings fall within valid ranges. Over-the-threshold settings may lead to a crash without being detected while under-the-threshold values may result in frequent false alarms and increase the operating costs. In the end, we also demonstrate three case studies to discuss that stealthy attacks may decrease the profits from 0.06% to 41%, depending on the ratio of costs and sales prices.
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Книги з теми "Stealthy attacks on ICS"

1

Inc, Game Counselor. Game Counselor's Answer Book for Nintendo Players. Redmond, USA: Microsoft Pr, 1991.

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2

Sepowski, Stephen J., ed. The Ultimate Hint Book. Old Saybrook, CT: The Ultimate Game Club Ltd., 1991.

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3

Ninja Science: Camouflage, Weapons, and Stealthy Attacks. Capstone, 2016.

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4

Lusted, Marcia Amidon. Ninja Science: Camouflage, Weapons, and Stealthy Attacks. Capstone, 2016.

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5

Lusted, Marcia Amidon. Ninja Science: Camouflage, Weapons, and Stealthy Attacks. Capstone, 2021.

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6

Lusted, Marcia Amidon. Ninja Science: Camouflage, Weapons and Stealthy Attacks. Raintree Publishers, 2016.

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7

Lusted, Marcia Amidon. Ninja Science: Camouflage, Weapons, and Stealthy Attacks. Capstone, 2021.

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8

Ninja Science: Camouflage, Weapons and Stealthy Attacks. Raintree Publishers, 2017.

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9

Lusted, Marcia Amidon. Ninja Science: Camouflage, Weapons, and Stealthy Attacks. Capstone, 2016.

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10

Inc, Game Counsellor, ed. The Game Counsellor's answer book for Nintendo Game players: Hundredsof questions -and answers - about more than 250 popular Nintendo Games. Redmond, Washington: Microsoft Press, 1991.

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Частини книг з теми "Stealthy attacks on ICS"

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Kleinmann, Amit, Ori Amichay, Avishai Wool, David Tenenbaum, Ofer Bar, and Leonid Lev. "Stealthy Deception Attacks Against SCADA Systems." In Computer Security, 93–109. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-72817-9_7.

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Osman, Amr, Jeannine Born, and Thorsten Strufe. "Mitigating Internal, Stealthy DoS Attacks in Microservice Networks." In Lecture Notes in Computer Science, 500–504. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91081-5_37.

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Sandberg, Henrik. "Stealthy False Data Injection Attacks in Feedback Systems Revisited." In Lecture Notes in Control and Information Sciences, 61–78. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65048-3_4.

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4

Stewin, Patrick. "Study of a Stealthy, Direct Memory Access Based Malicious Software." In Detecting Peripheral-based Attacks on the Host Memory, 33–52. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13515-1_4.

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de Meulenaer, Giacomo, and François-Xavier Standaert. "Stealthy Compromise of Wireless Sensor Nodes with Power Analysis Attacks." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 229–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16644-0_21.

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Al-Shaer, Ehab, and Syed Fida Gillani. "Agile Virtual Infrastructure for Cyber Deception Against Stealthy DDoS Attacks." In Cyber Deception, 233–57. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32699-3_10.

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Stewin, Patrick. "A Primitive for Revealing Stealthy Peripheral-Based Attacks on the Computing Platform’s Main Memory." In Research in Attacks, Intrusions, and Defenses, 1–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41284-4_1.

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Tian, Jiwei, Buhong Wang, Tengyao Li, Fute Shang, Kunrui Cao, and Jing Li. "Stealthy and Sparse False Data Injection Attacks Based on Machine Learning." In Cyberspace Safety and Security, 337–47. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-37337-5_27.

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Anwar, Adnan, Abdun Naser Mahmood, and Mark Pickering. "Data-Driven Stealthy Injection Attacks on Smart Grid with Incomplete Measurements." In Intelligence and Security Informatics, 180–92. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31863-9_13.

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Oswald, David. "Side-Channel Attacks on SHA-1-Based Product Authentication ICs." In Smart Card Research and Advanced Applications, 3–14. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31271-2_1.

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Тези доповідей конференцій з теми "Stealthy attacks on ICS"

1

Papadimitratos, Panagiotis, and Jing Deng. "Stealthy pre-attacks against random key pre-distribution security." In ICC 2012 - 2012 IEEE International Conference on Communications. IEEE, 2012. http://dx.doi.org/10.1109/icc.2012.6364226.

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Tang, Jin, and Yu Cheng. "Quick Detection of Stealthy SIP Flooding Attacks in VoIP Networks." In ICC 2011 - 2011 IEEE International Conference on Communications. IEEE, 2011. http://dx.doi.org/10.1109/icc.2011.5963248.

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Liu, H., and M. S. Kim. "Real-Time Detection of Stealthy DDoS Attacks Using Time-Series Decomposition." In ICC 2010 - 2010 IEEE International Conference on Communications. IEEE, 2010. http://dx.doi.org/10.1109/icc.2010.5501975.

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Hartmann, Laura, and Steffen Wendzel. "How Feasible are Steganographic and Stealth Attacks on TIA Project Metadata of ICS: A Case Study with Real-world Data." In EICC '21: European Interdisciplinary Cybersecurity Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3487405.3487661.

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Kelly, Janiece, Seth Richter, and Mina Guirguis. "Stealthy attacks on pheromone swarming." In 2013 IEEE International Multi-Cognitive Methods in SituationDisciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA 2013). IEEE, 2013. http://dx.doi.org/10.1109/cogsima.2013.6523861.

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Annavaram, Devakumar, Subham Sahoo, and Sukumar Mishra. "Stealth Attacks in Microgrids: Modeling Principles and Detection." In 2021 9th IEEE International Conference on Power Systems (ICPS). IEEE, 2021. http://dx.doi.org/10.1109/icps52420.2021.9670061.

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Teixeira, Andre, Iman Shames, Henrik Sandberg, and Karl H. Johansson. "Revealing stealthy attacks in control systems." In 2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 2012. http://dx.doi.org/10.1109/allerton.2012.6483441.

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Rath, Suman, Ioannis Zografopoulos, and Charalambos Konstantinou. "Stealthy Rootkit Attacks on Cyber-Physical Microgrids." In e-Energy '21: The Twelfth ACM International Conference on Future Energy Systems. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3447555.3466576.

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Goes, Romulo Meira, Eunsuk Kang, Raymond Kwong, and Stephane Lafortune. "Stealthy deception attacks for cyber-physical systems." In 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE, 2017. http://dx.doi.org/10.1109/cdc.2017.8264281.

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Aqil, Azeem, Ahmed O. F. Atya, Trent Jaeger, Srikanth V. Krishnamurthy, Karl Levitt, Patrick D. McDaniel, Jeff Rowe, and Ananthram Swami. "Detection of stealthy TCP-based DoS attacks." In MILCOM 2015 - 2015 IEEE Military Communications Conference. IEEE, 2015. http://dx.doi.org/10.1109/milcom.2015.7357467.

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Ми пропонуємо знижки на всі преміум-плани для авторів, чиї праці увійшли до тематичних добірок літератури. Зв'яжіться з нами, щоб отримати унікальний промокод!

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