{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,11]],"date-time":"2024-08-11T15:50:51Z","timestamp":1723391451623},"reference-count":52,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012190","name":"Ministry of Science and Higher Education of the Russian Federation","doi-asserted-by":"publisher","award":["075-15-2020-934"],"id":[{"id":"10.13039\/501100012190","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"Modern cyber-physical systems (CPS) use digital control of physical processes. This allows attackers to conduct various cyberattacks on these systems. According to the current trends, an information security monitoring system (ISMS) becomes part of a security management system of CPS. It provides information to make a decision and generate a response. A large number of new methods are aimed at CPS security, including security assessment, intrusion detection, and ensuring sustainability. However, as a cyber-physical system operates over time, its structure and requirements may change. The datasets available for the protection object (CPS) and the security requirements have become dynamic. This dynamic effect causes asymmetry between the monitoring data collection and processing subsystem and the presented security tasks. The problem herein is the choice of the most appropriate set of methods in order to solve the security problems of a particular CPS configuration from a particular bank of the available methods. To solve this problem, the authors present a method for the management of an adaptive information security monitoring system. The method consists of solving a multicriteria discrete optimization problem under Pareto-optimality conditions when the available data, methods or external requirements change. The experimental study was performed on an example of smart home intrusion detection. In the study, the introduction of a constraint (a change in requirements) led to the revision of the monitoring scheme and a different recommendation of the monitoring method. As a result, the information security monitoring system gains the property of adaptability to changes in tasks and the available data. An important result from the study is the fact that the monitoring scheme obtained using the proposed management method has a proven optimality under the given conditions. Therefore, the asymmetry between the information security monitoring data collection and processing subsystem and the set of security requirements in cyber-physical systems can be overcome.<\/jats:p>","DOI":"10.3390\/sym13122425","type":"journal-article","created":{"date-parts":[[2021,12,16]],"date-time":"2021-12-16T02:47:36Z","timestamp":1639622856000},"page":"2425","source":"Crossref","is-referenced-by-count":9,"title":["Key Concepts of Systemological Approach to CPS Adaptive Information Security Monitoring"],"prefix":"10.3390","volume":"13","author":[{"given":"Maria","family":"Poltavtseva","sequence":"first","affiliation":[{"name":"Institute of Cybersecurity and Information Protection, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia"}]},{"given":"Alexander","family":"Shelupanov","sequence":"additional","affiliation":[{"name":"Department of Comprehensive Information Security of Electronic Computer Systems, Tomsk State University of Control Systems and Radioelectronics, 634050 Tomsk, Russia"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-0875-3301","authenticated-orcid":false,"given":"Dmitriy","family":"Bragin","sequence":"additional","affiliation":[{"name":"Department of Comprehensive Information Security of Electronic Computer Systems, Tomsk State University of Control Systems and Radioelectronics, 634050 Tomsk, Russia"}]},{"given":"Dmitry","family":"Zegzhda","sequence":"additional","affiliation":[{"name":"Institute of Cybersecurity and Information Protection, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia"}]},{"given":"Elena","family":"Alexandrova","sequence":"additional","affiliation":[{"name":"Institute of Cybersecurity and Information Protection, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,15]]},"reference":[{"key":"ref_1","unstructured":"(2021, November 25). Analiz Gromkih Incidentov v Sfere Informacionnoj Bezopasnosti v 2019 Godu [Elektronnyj Resurs]. Available online: https:\/\/www.tadviser.ru\/a\/498885."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Dehghani, M., Niknam, T., Ghiasi, M., Siano, P., Haes Alhelou, H., and Al-Hinai, A. (2021). Fourier Singular Values-Based False Data Injection Attack Detection in AC Smart-Grids. Appl. Sci., 11.","DOI":"10.3390\/app11125706"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"112301","DOI":"10.1007\/s11432-020-2975-6","article-title":"Efficient privacy-preserving user authentication scheme with forward secrecy for industry 4.0","volume":"65","author":"Wang","year":"2022","journal-title":"Sci. China Inf. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"9390","DOI":"10.1109\/TVT.2020.2971254","article-title":"Unified Biometric Privacy Preserving Three-Factor Authentication and Key Agreement for Cloud-Assisted Autonomous Vehicles","volume":"69","author":"Jiang","year":"2020","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_5","unstructured":"Li, Z., Wang, D., and Morais, E. (2020). Quantum-Safe Round-Optimal Password Authentication for Mobile Devices. IEEE Trans. Dependable Secur. Comput. Early Access, 1\u201314."},{"key":"ref_6","unstructured":"Stevens, M. (2005, January 9\u201311). Security Information and Event Management (SIEM). Proceedings of the NEbraska CERT Conference, Omaha, NE, USA. Available online: http:\/\/www.certconf.org\/presentations\/2005\/files\/WC4.pdf."},{"key":"ref_7","first-page":"2","article-title":"Primenenie tekhnologii upravleniya informaciej i sobytiyami bezopasnosti dlya zashchity informacii v kriticheski vazhnyh infrastrukturah","volume":"1","author":"Kotenko","year":"2012","journal-title":"Trudy SPIIRAN Vyp"},{"key":"ref_8","first-page":"51","article-title":"Podhod k razrabotke SIEM-sistemy dlya Interneta veshchej","volume":"2","author":"Lavrova","year":"2016","journal-title":"Probl. Inf. Bezopasnosti. Komp\u2019yuternye Sist."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"387","DOI":"10.3103\/S0146411619050067","article-title":"Approach to Presenting Network Infrastructure of Cyberphysical Systems to Minimize the Cyberattack Neutralization Time","volume":"53","author":"Lavrova","year":"2019","journal-title":"Autom. Control Comp. Sci."},{"key":"ref_10","unstructured":"Klyanchin, A.I., Markov, A.S., Fadin, A.A., and Ilyuhin, M.V. (2013, January 29\u201330). SIEM\u2013tekhnologiya kak osnova postroeniya zashchishchennyh system. Informatizaciya i informacionnaya bezopasnost\u2019 pravoohranitel\u2019nyh organov. Proceedings of the XXII Vserossijskaya Nauchnaya Konferenciya, Moskva, Russia. Available online: https:\/\/www.elibrary.ru\/item.asp?id=24711035."},{"key":"ref_11","first-page":"1","article-title":"Primenenie analiticheskih sredstv v sisteme operacionnogo monitoringa i analiza bezopasnosti kiberfizicheskih sistem dlya predpriyatij toplivno-energeticheskogo kompleksa, Matematicheskie metody v tekhnike i tekhnologiyah","volume":"2","author":"Nashivochnikov","year":"2019","journal-title":"MMTT-32"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Siddiqui, S., Khan, M.S., Ferens, K., and Kinsner, W. (2017, January 26\u201328). Fractal based cognitive neural network to detect obfuscated and indistinguishable internet threats. Proceedings of the 2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC), Oxford, UK.","DOI":"10.1109\/ICCI-CC.2017.8109765"},{"key":"ref_13","unstructured":"Eric, D., and Knapp, J.T. (2015). Chapter 12-Security Monitoring of Industrial Control Systems. Industrial Network Security, Syngress. [2nd ed.]."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"47374","DOI":"10.1109\/ACCESS.2018.2866403","article-title":"Data-Driven Monitoring and Safety Control of Industrial Cyber-Physical Systems: Basics and Beyond","volume":"6","author":"Jiang","year":"2018","journal-title":"IEEE Access"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3076253","article-title":"Data Science: A Comprehensive Overview","volume":"50","author":"Cao","year":"2017","journal-title":"ACM Comput. Surv."},{"key":"ref_16","unstructured":"Solar JSOC Security Report (2021, November 25). Itogi 2019 Goda [Elektronnyj Resurs]. Available online: https:\/\/rt-solar.ru\/upload\/iblock\/faf\/Solar-JSOC-Security-Report-2019.pdf."},{"key":"ref_17","unstructured":"Kiberataki na Sistemy ASU TP v Energetike v Evrope (2021, November 25). Pervyj Kvartal 2020 Goda [Elektronnyj Resurs]. Available online: https:\/\/ics-cert.kaspersky.ru\/reports\/2020\/09\/03\/cyberthreats-for-ics-in-energy-in-europe-q1-2020\/."},{"key":"ref_18","unstructured":"GOST R 50922-2006 Zashchita Informacii (2021, November 25). Osnovnye Terminy i Opredeleniya Utverzhden i Vveden v Dejstvie Prikazom Federal\u2019nogo Agentstva po Tekhnicheskomu Regulirovaniyu i Metrologii ot 27 dekabrya 2006 g. N 373-st. Available online: https:\/\/docs.cntd.ru\/document\/1200058320."},{"key":"ref_19","unstructured":"Lukackij, A. (2020). Izmerenie effektivnosti SOC. Chast\u2019 2. Inf. Bezop., 3, Available online: https:\/\/www.itsec.ru\/articles\/izmerenie-effectivnosti-soc-part-2."},{"key":"ref_20","unstructured":"Proekt Standarta Zashchita Informacii (2021, November 25). Monitoring Informacionnoj Bezopasnosti. Obshchie Polozheniya\u00bb [Elektronnyj resurs]\u20132020., Available online: https:\/\/fstec.ru\/component\/attachments\/download\/243."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.chemolab.2017.09.021","article-title":"Review on data-driven modeling and monitoring for plant-wide industrial processes","volume":"171","author":"Ge","year":"2017","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Klir, G.J. (1985). Architecture of Systems Problem Solving, Plenum Publishing Corporation.","DOI":"10.1007\/978-1-4757-1168-4"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Wang, H., and Li, S. (2018). General Systems Theory and Systems Engineering. Introduction to Social Systems Engineering, Springer.","DOI":"10.1007\/978-981-10-7040-2_2"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1253","DOI":"10.1016\/j.promfg.2017.09.047","article-title":"Network and information security challenges within Industry 4.0 paradigm","volume":"13","author":"Pereira","year":"2017","journal-title":"Procedia Manuf."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Chhetri, S.R. (2020). Abdullah, M. Data-Driven Modeling of Cyber-Physical Systems Using Side-Channel Analysis, Springer Nature.","DOI":"10.1007\/978-3-030-37962-9"},{"key":"ref_26","unstructured":"Zhao, Z., Huang, Y., Zhen, Z., and Li, Y. (2021, November 25). Data-Driven False Data-Injection Attack Design and Detection in Cyber-Physical Systems. IEEE Trans. Cybern. Early Access 2020, 1\u20139. Available online: https:\/\/ieeexplore.ieee.org\/abstract\/document\/9003529."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"968","DOI":"10.3103\/S0146411620080283","article-title":"Building an Adaptive System for Collecting and Preparing Data for Security Monitoring","volume":"54","author":"Poltavtseva","year":"2020","journal-title":"Autom. Control Comp. Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"131","DOI":"10.15514\/ISPRAS-2020-32(5)-10","article-title":"Heterogeneous data aggregation and normalization in information security monitoring and intrusion detection systems of large-scale industrial CPS","volume":"32","author":"Poltavtseva","year":"2020","journal-title":"Proc. Inst. Syst. Program. RAS"},{"key":"ref_29","unstructured":"Podinovskij, V.V., and Nogin, V.D. (2007). Pareto\u2013Optimal\u2019nye Resheniya Mnogokriterialnyh Zadach, Fizmatlit."},{"key":"ref_30","first-page":"98","article-title":"Problema suzheniya mnozhestva Pareto: Podhody k resheniyu","volume":"1","author":"Nogin","year":"2008","journal-title":"Iskusstv. Intell. i Prinyatie Reshenij"},{"key":"ref_31","first-page":"61","article-title":"Risk\u2013orientirovannyj podhod k organizacii kontrolya v podsistemah obespecheniya bezopasnosti informacionnyh system","volume":"3","author":"Anisimov","year":"2016","journal-title":"Probl. Inf. Bezopasnosti. Komp\u2019yuternye Sist."},{"key":"ref_32","unstructured":"Krundyshev, V.M., and Kalinin, M.O. (2020). Metodika analiza riskov informacionnoj bezopasnosti dlya intellektual\u2019nyh kibersred, Fundamental\u2019nye Problemy Upravleniya Proizvodstvennymi Processami v Usloviyah Perekhoda k Industrii 4.0. Tezisy Dokladov Nauchnogo Seminara v Ramkah Mezhdunarodnoj Nauchno-Tekhnicheskoj Konferencii \u201c\\Avtomatizaciya\\\u201d."},{"key":"ref_33","first-page":"48","article-title":"Mul\u2019tifraktal\u2019nyj analiz trafika magistral\u2019nyh setej internet dlya obnaruzheniya atak otkaza v obsluzhivanii, Problemy informacionnoj bezopasnosti","volume":"2","author":"Zegzhda","year":"2018","journal-title":"Komp\u2019yuternye Sist."},{"key":"ref_34","first-page":"174","article-title":"Detection of Teletraffic Anomalies Using Multifractal Analysis","volume":"3","author":"Sheluhin","year":"2011","journal-title":"Int. J. Adv. Comput. Technol."},{"key":"ref_35","first-page":"48","article-title":"Security Monitoring for Industrial Control Systems","volume":"Volume 9588","author":"Coletta","year":"2015","journal-title":"Security of Industrial Control Systems and Cyber Physical Systems"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"13","DOI":"10.21681\/2311-3456-2019-2-13-20","article-title":"Modelirovanie setevoj infrastruktury slozhnyh ob\u201dektov dlya resheniya zadachi protivodejstviya kiberatakam","volume":"2","author":"Lavrova","year":"2019","journal-title":"Vopr. Kiberbezopasnosti"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Havarneanu, G., Setola, R., Nassopoulos, H., and Wolthusen, S. (2017). A Dataset to Support Research in the Design of Secure Water Treatment Systems. Critical Information Infrastructures Security, Springer. Lecture Notes in Computer Science;.","DOI":"10.1007\/978-3-319-71368-7"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"16488","DOI":"10.1109\/ACCESS.2021.3051300","article-title":"Cyber Attack Detection Based on Wavelet Singular Entropy in AC Smart Islands: False Data Injection Attack","volume":"9","author":"Dehghani","year":"2021","journal-title":"IEEE Access"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3514","DOI":"10.1109\/TSG.2021.3066316","article-title":"Cyber-Physical Anomaly Detection for Wide-Area Protection Using Machine Learning","volume":"12","author":"Singh","year":"2021","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Paredes, C.M., Mart\u00ednez-Castro, D., Ibarra-Junquera, V., and Gonz\u00e1lez-Potes, A. (2021). Detection and Isolation of DoS and Integrity Cyber Attacks in Cyber-Physical Systems with a Neural Network-Based Architecture. Electronics, 10.","DOI":"10.3390\/electronics10182238"},{"key":"ref_41","unstructured":"Kutz, J.N. (2013). Data-Driven Modeling & Scientific Computation: Methods for Complex Systems & Big Data, OUP."},{"key":"ref_42","unstructured":"Kondrat\u2019eva, N.V., and Valeev, S.S. (2016, January 16). Modelirovanie zhiznennogo cikla slozhnogo tekhnicheskogo ob\u201dekta na osnove koncepcii bol\u2019shih dannyh. Proceedings of the 3rd Russian Conference. Mathematical Modeling and Information Technologies, Yekaterinburg, Russia."},{"key":"ref_43","first-page":"27","article-title":"Obnaruzhenie anomalij v komp\u2019yuternyh setyah s ispol\u2019zovaniem metodov mashinnogo obucheniya","volume":"1","year":"2020","journal-title":"REDS Telekommun. Ustrojstva i Sist."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Karimipour, H., Srikantha, P., Farag, H., and Wei-Kocsis, J. (2020). Learning Based Anomaly Detection in Critical Cyber-Physical Systems. Security of Cyber-Physical Systems, Springer.","DOI":"10.1007\/978-3-030-45541-5"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Khanna, A., Gupta, D., Bhattacharyya, S., Hassanien, A.E., Anand, S., and Jaiswal, A. (2022). A Systematic Review on Various Attack Detection Methods for Wireless Sensor Networks. International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, Springer.","DOI":"10.1007\/978-981-16-2594-7"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Haque, N.I., Shahriar, M.H., Dastgir, M.G., Debnath, A., Parvez, I., Sarwat, A., and Rahman, M.A. (2021, January 11\u201313). A Survey of Machine Learning-based Cyber-physical Attack Generation, Detection, and Mitigation in Smart-Grid. Proceedings of the 2020 52nd North American Power Symposium (NAPS), Tempe, AZ, USA.","DOI":"10.1109\/NAPS50074.2021.9449635"},{"key":"ref_47","unstructured":"Zhang, J., Pan, L., Han, Q.-L., Chen, C., Wen, S., and Xiang, Y. (2021). Deep Learning Based Attack Detection for Cyber-Physical System Cybersecurity: A Survey. IEEE\/CAA J. Autom. Sin., 1\u201315."},{"key":"ref_48","first-page":"1","article-title":"A survey on attack detection, estimation and control of industrial cyber\u2013physical systems","volume":"16","author":"Zhang","year":"2021","journal-title":"ISA Trans."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Akowuah, F., and Kong, F. (2021, January 7). Real-Time Adaptive Sensor Attack Detection in Autonomous Cyber-Physical Systems. Proceedings of the 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium (RTAS), Nashville, TN, USA.","DOI":"10.1109\/RTAS52030.2021.00027"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"29429","DOI":"10.1109\/ACCESS.2021.3059042","article-title":"Cyber-Attack Detection and Cyber-Security Enhancement in Smart DC-Microgrid Based on Blockchain Technology and Hilbert Huang Transform","volume":"9","author":"Ghiasi","year":"2021","journal-title":"IEEE Access"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1109\/MSMC.2020.3049092","article-title":"Observer-Based Attack Detection and Mitigation for Cyberphysical Systems: A Review","volume":"7","author":"Kordestani","year":"2021","journal-title":"IEEE Syst. Man Cybern. Mag."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Dehghani, M., Niknam, T., Ghiasi, M., Bayati, N., and Savaghebi, M. (2021). Cyber-Attack Detection in DC Microgrids Based on Deep Machine Learning and Wavelet Singular Values Approach. Electronics, 10.","DOI":"10.3390\/electronics10161914"}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/13\/12\/2425\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,23]],"date-time":"2024-07-23T02:22:21Z","timestamp":1721701341000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/13\/12\/2425"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,15]]},"references-count":52,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2021,12]]}},"alternative-id":["sym13122425"],"URL":"https:\/\/doi.org\/10.3390\/sym13122425","relation":{},"ISSN":["2073-8994"],"issn-type":[{"value":"2073-8994","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,15]]}}}