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Tushkanova Olga Nickolaevna

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Programs and databases

2020

1. Olga Tushkanova, Andrey Chechulin Component for the classification of social network posts. Certificate No. 2020666209. Registered in the Computer Program Registry 07.12.2020.

   

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Former Projects

• Andrey Chechulin (Principal Investigator). Grant of Russian Science Foundation № 18-71-10094-P "Monitoring and counteraction to malicious influence in the information space of social networks", 2021-2023 (Researcher).

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Books and Chapters in Books

1. A.F. Volynsky, V.P, Lavrov, T.V. Averyanova, I.A. Arkhipova, A.A. Bokov, N.T. Vedernikov, Yu.V. Gavrilin, A.Yu.Golovin, V.N. Grigoriev, V.A. Zhbankov, A.M. Zinin, Yu.G. Korukhov, A.M. Kustov, V.O. Lapin, N.P. Mailis, T.F. Moiseeva, A.S. Podshibyakin, L.N. Poselskaya, I.V. Tishutina, O.N. Tushkanova, etc. Criminalistics // Textbook for university students / Ser. Law and law. (2nd edition, revised and expanded) Moscow, 2015. 943p. // https://elibrary.ru/item.asp?id=36908316

Papers

2024

1. M. Kolomeets, O. Tushkanova, V. Desnitsky, L. Vitkova, A. Chechulin. Experimental evaluation: can humans recognise social media bots? // Big Data and Cognitive Computing. 2024. Т. 8. № 3. С. 24. DOI: 10.3390/bdcc8030024 // https://elibrary.ru/item.asp?id=66173046

2023

1. Dmitry Levshun, Olga Tushkanova, Andrey Chechulin. Two-model active learning approach for inappropriate information classification in social networks // International Journal of Information Security. 2023. Т. 22. № 6. С. 1921-1936. DOI:10.1007/s10207-023-00726-7 // https://elibrary.ru/item.asp?id=63329930
2. O. Tushkanova, D. Levshun, A. Branitskiy, E. Fedorchenko, E. Novikova, I. Kotenko. Detection of Cyberattacks and Anomalies in Cyber-Physical Systems: Approaches, Data Sources, Evaluation // Algorithms, vol. 16, no. 2, 2023, pp. 85. DOI: 10.3390/a16020085.// https://www.elibrary.ru/item.asp?id=60517408

2022

1. Elena Doynikova, Evgenia Novikova, Ivan Murenin, Maxim Kolomeec, Diana Gaifulina, Olga Tushkanova, Dmitry Levshun, Alexey Meleshko, Igor Kotenko. Security Measuring System for IoT Devices // Lecture Notes in Computer Science. 2022. Т. 13106 LNCS. С. 256-275. DOI: 10.1007/978-3-030-95484-0_16 // https://elibrary.ru/item.asp?id=48184836
2. Dmitry Levshun, Olga Tushkanova, Andrey Chechulin. Active learning approach for inappropriate information classification in social networks // Proceedings of the 30th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP 2022). P. 283-289. DOI: 10.1109/PDP55904.2022.00050. // https://elibrary.ru/item.asp?id=48582978
3. E.V. Fedorchenko (Doynikova), E.S. Novikova, I.V. Kotenko, D.A. Gayfulina, O.N. Tushkanova, D.S. Levshun, A.V. Meleshko , I.N. Murenin, M.V. Kolomeets. The security and privacy measuring system for the internet of things devices // Cybersecurity issues. 2022. No. 5 (51). pp. 28-46. DOI: 10.21681/2311-3456-2022-5-28-46 // https://elibrary.ru/item.asp?id=50310106 (in Russian).
4. M.V. Kolomiets, L.A. Vitkova, O.N. Tushkanova, A.A. Chechulin. Experimental evaluation: can humans recognize social media bots? // Networks in the Global World 2022, - (2022).

2021

1. Maxim Kolomeets, Olga Tushkanova, Dmitry Levshun, Andrey Chechulin. Camouflaged bot detection using the friend list // Proceedings - 29th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2021. 29. 2021. С. 253-259. DOI: 10.1109/PDP52278.2021.00048 // https://elibrary.ru/item.asp?id=46047553 (Scopus).
2. Olga Tushkanova, Vladimir Gorodetsky. Learning an ontology of text data // В сборнике: CEUR Workshop Proceedings. 10. Сер. "IMSC 2021 - Russian Advances in Fuzzy Systems and Soft Computing: Selected Contributions to the 10th International Conference on "Integrated Models and Soft Computing in Artificial Intelligence", Kolomna, May 17-20, 2021 P. 37-44. (Scopus) // https://elibrary.ru/item.asp?id=47511846
3. O.N. Tushkanova. Identification of potentially malicious posts on social networks using positive and unlabeled learning on text data // Control systems, communications and security. 2021. No. 6. pp. 30-52. DOI: 10.24412/2410-9916-2021-6-30-52 // https://elibrary.ru/item.asp?id=47416443 (in Russian).
4. V.I. Gorodetsky, O.N.Tushkanova. Generation of text data ontology // In the collection: Integrated Models and Soft computing in Artificial Intelligence (IMB-2021). Collection of scientific papers of the Xth International Scientific and Technical Conference. In 2 volumes. Smolensk, 2021. pp. 284-295 // https://elibrary.ru/item.asp?id=46337304 (in Russian).

2020

1. Lidia Vitkova, Igor Saenko, Olga Tushkanova. An Approach to Creating an Intelligent System for Detecting and Countering Inappropriate Information on the Internet // Studies in Computational Intelligence 2020. Vol. 868 pp. 244-254. https://doi.org/10.1007/978-3-030-32258-8_29. ISSN 1860-949X. // https://elibrary.ru/item.asp?id=43219363
2. A. Soboleva, O. Tushkanova. The Methodology of Extraction and Analysis of Event Log Social Graph // Conference of Open Innovations Association, FRUCT. 2020. № 26. P. 415-422 // https://elibrary.ru/item.asp?id=42830762
3. Igor Kotenko, Lidiya Vitkova, Igor Saenko, Olga Tushkanova, Alexander Branitskiy. The intelligent system for detection and counteraction of malicious and inappropriate information on the Internet // AI Communications. 2020. Vol. 33 №. 1. pp. 13-25. DOI: 10.3233/AIC-200647 // https://elibrary.ru/item.asp?id=45174880 (WoS, Scopus)
4. Vladimir Gorodetsky, Olga Tushkanova. Semantic Technologies for Semantic Applications. Part 2. Models of Comparative Text Semantics // Scientific and Technical Information Processing. 2020. Т. 47. № 6. С. 365-373 DOI: 10.3103/S0147688220060027 (WoS, Scopus) // https://elibrary.ru/item.asp?id=46755444
5. Lidia Vitkova, Igor Kotenko, Maxim Kolomeets, Olga Tushkanova, Andrey Chechulin. Hybrid Approach for Bots Detection in Social Networks Based on Topological, Textual and Statistical Features // Conference: 4th International Scientific Conference “Intelligent Information Technologies for Industry”At: Ostrava-Prague, Czech Republic. May 2020 // Advances in Intelligent Systems and Computing, Springer. 2020. vol.1156 AISC . P.412-421. DOI:10.1007/978-3-030-50097-9_42 // https://elibrary.ru/item.asp?id=45439091
6. I. B. Paraschuk, V. A. Desnitsky, O. N. Tushkanova. Model of the digital content parental control system on the Internet // XVII St. Petersburg International Conference " Regional Informatics (RI-2020)". St. Petersburg, October 28-30, 2020, part 1., pp. 168-170 http://www.spoisu.ru/files/ri/ri2020/ri2020_materials_1.pdf // https://www.elibrary.ru/item.asp?id=49390765 (in Russian).

2019

1. V. Gorodetsky, O. Tushkanova. Semantic Technologies for Semantic Applications. Part 1. Basic Components of Semantic Technologies // Scientific and Technical Information Processing, Vol..46 № 5, Р.306-313 DOI: 10.3103/S0147688219050022 // https://elibrary.ru/item.asp?id=43267255
2. Olga Tushkanova, Vladimir Samoylov. Knowledge Net: Model and System for Accumulation, Representation, and Use of Knowledge // IFAC-PapersOnLine. 9th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2019. 2019. С. 1150-1155. // https://elibrary.ru/item.asp?id=43250613
3. Vladimir Gorodetsky, Olga Tushkanova. Semantic technologies for semantic applications. Part 2. Models of comparative text semantics // Artificial Intelligence and Decision Making. 2019.No 1. C. 49-61. (VAK, RSCI, impact factor - 0.74). DOI 10.14357 / 20718594190105 // https://elibrary.ru/item.asp?id=37179703 (in Russian).
4. Dmitry Kudryavtsev, Alena Begler, Tatiana Gavrilova, Irina Leshcheva, Miroslav Kubelsky, Olga Tushkanova. Method for collaborative visual creation of a knowledge graph // Artificial Intelligence and Decision Making. 2019.No 1. P. 27-38. (VAK, RSCI, impact factor - 0.74). DOI 10.14357 / 20718594190103 // https://elibrary.ru/item.asp?id=37179701 (in Russian).
5. Olga Tushkanova, Vladimir Samoylov. Knowledge Net: model and system for accumulation, representation and use of knowledge and data. Ontology of designing. 2019; Vol. 9. № 1 (31) P. 117-131. (VAK, RSCI). DOI: 10.18287/2223-9537-2019-9-1-117-131 // https://elibrary.ru/item.asp?id=37627844 (in Russian).
6. Igor Kotenko, Olga Tushkanova. A version of the system architecture for analyzing information objects on the Internet using parallel computing // VIII International Scientific-Technical and Scientific-Methodological Conference "Actual Problems of Information Telecommunications in Science and Education" (APINO 2019). 2019. vol. 1. pp. 577-580. https://www.sut.ru/doci/nauka/1AEA/APINO/8-APINO%202019.%20Т.1.pdf // https://elibrary.ru/item.asp?id=41383598 (in Russian).
7. Olga Tushkanova, Igor Saenko. The Technique of ensuring timeliness of multiclass classification of inappropriate information on the Internet using parallel computing // XI St. Petersburg Interregional Conference «Information Security of Russian Regions», October 23-25, 2019, Russia, St. Petersburg. 2019. pp. 153-155. http://www.spoisu.ru/files/ibrr/ibrr2019/ibrr2019_materials.pdf // https://elibrary.ru/item.asp?id=45842703 (in Russian).

2018

1. D. Kudryavtsev, T. Gavrilova, I. Leshcheva, A. Begler, M. Kubelskiy, O. Tushkanova. Mind mapping and spreadsheets in collaborative design of knowledge graphs // CEUR Workshop Proceedings. 17, Business Resilience - Organizational and Information System Resilience in Congruence. Сер. "BIR-WS 2018 - Joint Proceedings of the BIR 2018 Short Papers, Workshops and Doctoral Consortium, co-located with 17th International Conference Perspectives in Business Informatics Research, BIR 2018" 2018. С. 82-93 // https://elibrary.ru/item.asp?id=38646475
2. D.V. Kudryavtsev, T.A. Gavrilova, I.A. Leshcheva, A. Begler, M. Kubelski, O. Tushkanova. A method for collaborative visual creation of a knowledge graph // GSOM EMERGING MARKETS CONFERENCE 2018. Conference Proceedings. Graduate School of Management, Saint Petersburg University. 2018. С. 98-102. // https://elibrary.ru/item.asp?id=41821719
3. Vladimir Gorodetski, Olga Tushkanova. Semantic technologies for semantic application. Part 1. Basic components of semantic technologies // Artificial Intelligence and Decision Making. 2018. No.4. P.61-71 DOI: 10.14357/20718594180406 // https://elibrary.ru/item.asp?id=36643713 (in Russian).
4. V.I. Gorodetsky, O.N. Tushkanova. Semantic technologies for semantic applications. Part 1. Basic components of semantic technologies // Artificial intelligence and decision-making. 2018. No. 4. pp. 61-71. DOI: 10.14357/20718594180406 // https://elibrary.ru/item.asp?id=36643713 (in Russian).
5. V.I. Gorodetsky, O.N. Tushkanova. Semantic computing and big data // Materials of the plenary sessions of the 11th Russian Multi-conference on management problems. St. Petersburg: JSC "Concern" Central Research Institute "Electropribor", 2018, p. 55-71 // https://elibrary.ru/item.asp?id=36591593 (in Russian).
6. D.V. Kudryavtsev, T.A. Gavrilova, I.A. Leshcheva, A.M. Begler, M.V. Kubelsky, O.N. Tushkanova. Methodology of group work on visual development of the knowledge graph // In the collection: The Sixteenth National Conference on Artificial Intelligence with international participation CII-2018. Proceedings of the conference: in 2 volumes. 2018. pp. 53-60. // https://elibrary.ru/item.asp?id=35568575 (in Russian).

2016

1. Gorodetsky V.I., Tushkanova O.N. Effective Big Data Processing Techniques for Decision Making // In the collection: The 9th Russian Multi-conference on Management Problems. materials of the plenary sessions. SSC RF JSC "Concern "Central Research Institute "Electropribor". 2016. pp. 74-96. // https://elibrary.ru/item.asp?id=26797583 (in Russian).
2. V.I. Gorodetsky, O.N. Tushkanova. Big data technology // In the book: Promising directions of development of domestic information technologies. materials of the II interregional scientific and practical conference. Sevastopol State University; scientific ed. by B.V. Sokolov. 2016. pp. 15-17. // https://elibrary.ru/item.asp?id=27558832 (in Russian).

2015

1. O. Tushkanova. Comparative analysis of the numerical measures for mining associative and causal relationships in big data // Communications in Computer and Information Science. 2015. Т. 535. С. 571-582 DOI: 10.1007/978-3-319-23766-4_45 // https://elibrary.ru/item.asp?id=26927658
2. V. Gorodetsky, V. Samoylov, O. Tushkanova. Agent-based customer profile learning in 3G recommender systems: ontology-driven multi-source cross-domain case // Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). 2015. С. 12-25. DOI: 10.1007/978-3-319-20230-3-2 // https://elibrary.ru/item.asp?id=23992803
3. V. Gorodetsky, O. Tushkanova. Data-driven semantic concept analysis for user profile learning in 3G recommender systems // Proceedings - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2015. Big Data in Global Brain and Social Networks. 2015. С. 92-97 DOI: 10.1109/WI-IAT.2015.80 // https://elibrary.ru/item.asp?id=27153946
4. O. Tushkanova, V. Gorodetsky. Data-driven semantic concept analysis for automatic actionable ontology design // Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2015. 2015. С. 7344893 DOI: 10.1109/DSAA.2015.7344893 // https://elibrary.ru/item.asp?id=26996462
5. O.N. Tushkanova, V.I. Gorodetsky. Associative classification: analytical overview. Part 1 // Proceedings of SPIIRAN. 2015. No. 1 (38). pp. 183-203. // https://elibrary.ru/item.asp?id=23342080 (in Russian).
6. Tushkanova O.N., Gorodetsky V.I. Associative classification: analytical overview. Part 2// Proceedings of SPIIRAN. 2015. No. 2 (39). pp. 212-240. // https://elibrary.ru/item.asp?id=23388656 (in Russian).
7. O.N. Tushkanova. Experimental study of the numerical measures for mining associative and causal relationship in big data // Information technologies and computing systems. 2015. No. 3. pp. 23-32. // https://elibrary.ru/item.asp?id=25032417 (in Russian).

2014

1. V.I. Gorodetsky, O.N. Tushkanova. Ontology-based user profile personification in 3g recommender systems // Design ontology. 2014. No. 3 (13). pp. 7-31. // https://elibrary.ru/item.asp?id=21884863 (in Russian).

2012

1. N.V. Tushkanov, O.N. Tushkanova. Procedures of collective learning and self-organization in multisensory and multi-agent systems // In the collection: The 5th Russian Multi-conference on Management Problems. materials of the conference "Information Technologies in Management" (ITU-2012). 2012. pp. 253-258 // https://elibrary.ru/item.asp?id=21718380 (in Russian).

2011

1. N. Tushkanov, O. Tushkanova, V. Nazarov, A. Kuznetsova. Multi-sensor system of intellectual handling robot control on the basis of collective learning paradigm // Advances in Intelligent and Soft Computing. 2011. Т. 123. С. 195-200. DOI: 10.1007/978-3-642-25661-5_26 // https://elibrary.ru/item.asp?id=18031742
2. N.B. Tushkanov, A.V. Kuznetsova, V.A. Nazarov, O.N. Tushkanova, D.A. Lyubvin. Construction of multisensory systems of collective control and recognition // News of higher educational institutions. Electromechanics. 2011. No. 1. pp. 54-62. // https://elibrary.ru/item.asp?id=16209770 (in Russian).

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