Andrii Shalaginov
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- Associate Professor
- School of Economics, Innovation and Technology
Background
Andrii Shalaginov is an Associate Professor with the Department of Technology at the Kristiania University College. His research focus is the application of artificial intelligence for cybersecurity, detection of computer viruses, network attacks and protection of Internet of Things devices.
He holds a PhD degree in Information Security from the Norwegian University of Science and Technology (NTNU) and has been working at the Center for Cyber and Information Security (CCIS) on digital forensics.
Shalaginov has more than a decade of experience in cybersecurity, cybercrime investigation, intelligent malware detection and had served as a cybersecurity researcher for UNICRI on copyright-infringing websites detection and malware analysis.
He is also a nominated representative from Norway in COST Action CA17124 “DigForAsp” and a member of the “Impact of Technology” Expert Group hosted by the European Union Intellectual Property Office Observatory (EUIPO).
Areas of expertise
Employee details
Scientific Publications
- Jensen, Markus Wiik, Ren, Huamin & Shalaginov, Andrii (2024). Day-ahead Electricity Price Forecasting of Elspot markets in Norway. International Academy, Research and Industry Association (IARIA). ISBN 978-1-68558-139-8.
- Bhandari, Guru Prasad, Assres, Gebremariam Mesfin, Nikola, Gavric, Shalaginov, Andrii & Grønli, Tor-Morten (2024). IoTvulCode: AI-enabled vulnerability detection in software products designed for IoT applications. International Journal of Information Security. ISSN 1615-5262. doi: 10.1007/s10207-024-00848-6
- Gavric, Nikola, Bhandari, Guru & Shalaginov, Andrii (2024). Towards Resource-Efficient DDoS Detection in IoT: Leveraging Feature Engineering of System and Network Usage Metrics. Journal of Network and Systems Management. ISSN 1064-7570. 32(4) doi: 10.1007/s10922-024-09848-2
- Bhandari, Guru, Lyth, Andreas, Shalaginov, Andrii & Grønli, Tor-Morten (2023). Distributed Deep Neural-Network-Based Middleware for Cyber-Attacks Detection in Smart IoT Ecosystem: A Novel Framework and Performance Evaluation Approach. Electronics (Basel). ISSN 2079-9292. 12(2) doi: 10.3390/electronics12020298
- Balto, Karl Edvard Eriksen, Yamin, Muhammad Mudassar, Shalaginov, Andrii & Katt, Basel (2023). Hybrid IoT Cyber Range. Sensors. ISSN 1424-8220. 23(6) doi: 10.3390/s23063071
- Bouzidi, Mohammed, Gupta, Nishu, Alaya Cheikh, Faouzi, Shalaginov, Andrii & Derawi, Mohammad (2022). A Novel Architectural Framework on IoT Ecosystem, Security Aspects and Mechanisms: A Comprehensive Survey. IEEE Access. ISSN 2169-3536. 10 p {0}. doi: 10.1109/ACCESS.2022.3207472
- Cvitić, Ivan, Peraković, Dragan, Periša, Marko, Jevremović, Aleksandar & Shalaginov, Andrii (2022). An Overview of Smart Home IoT Trends and related Cybersecurity Challenges. Mobile Networks and Applications. ISSN 1383-469X. doi: 10.1007/s11036-022-02055-w
- Shalaginov, Andrii, Stamp, Mark & Alazab, Mamoun (2021). Malware Analysis Using Artificial Intelligence and Deep Learning. Springer. ISBN 978-3-030-62581-8. FULLTEKST
- Shalaginov, Andrii & Øverlier, Lasse (2021). A Novel Study on Multinomial Classification of x86/x64 Linux ELF Malware Types and Families Through Deep Neural Networks. I Shalaginov, Andrii, Stamp, Mark & Alazab, Mamoun (red.) Malware Analysis Using Artificial Intelligence and Deep Learning. Springer. ISBN 978-3-030-62581-8. p {0}. doi: 10.1007/978-3-030-62582-5_17
- Shalaginov, Andrii, Dyrkolbotn, Geir Olav & Alazab, Mamoun (2021). Review of the Malware Categorization in the Era of Changing Cybethreats Landscape: Common Approaches, Challenges and Future Needs. I Shalaginov, Andrii, Stamp, Mark & Alazab, Mamoun (red.) Malware Analysis Using Artificial Intelligence and Deep Learning. Springer. ISBN 978-3-030-62581-8. p {0}. doi: 10.1007/978-3-030-62582-5_3
- Jensen, Øyvind, Shalaginov, Andrii & Dyrkolbotn, Geir Olav (2021). Study of Blacklisted Malicious Domains from a Microsoft Windows End-user Perspective: Is It Safe Behind the Wall? Norsk Informasjonssikkerhetskonferanse (NISK). ISSN 1893-6563. (3) FULLTEKST
- Awuson-David, Kenny, Al-Hadhrami, Tawfik, Alazab, Mamoun, Shah, Nazaraf & Shalaginov, Andrii (2021). BCFL logging: An approach to acquire and preserve admissible digital forensics evidence in cloud ecosystem. Future Generation Computer Systems. ISSN 0167-739X. 122 p {0}. doi: 10.1016/j.future.2021.03.001
- Guo, Zhiwei, Tang, Lianggui, Guo, Tan, Yu, Keping, Alazab, Mamoun & Shalaginov, Andrii (2021). Deep Graph neural network-based spammer detection under the perspective of heterogeneous cyberspace. Future Generation Computer Systems. ISSN 0167-739X. 117 p {0}. doi: 10.1016/j.future.2020.11.028
- Shalaginov, Andrii & Azad, Muhammad Ajmal (2021). Securing resource-constrained iot nodes: Towards intelligent microcontroller-based attack detection in distributed smart applications. Future Internet. ISSN 1999-5903. 13(11) doi: 10.3390/fi13110272
- Shalaginov, Andrii & Grønli, Tor-Morten (2021). Securing Smart Future: Cyber Threats and Intelligent Means to Respond. I Chen, Yixin, Ludwig, Heiko, Tu, Yicheng, Fayyad, Usama, Zhu, Xingquan, Hu, Xiaohua, Byna, Surendra, Liu, Xiong, Zhang, Jianping, Pan, Shirui, Papalexakis, Vagelis, Wang, Jianwu, Cuzzocrea, Alfredo & Ordóñez, Carlos (red.) 2021 IEEE International Conference on Big Data. IEEE Press. ISBN 978-1-6654-3902-2. p {0}. doi: 10.1109/BigData52589.2021.9671703
- Yamin, Muhammad Mudassar, Shalaginov, Andrii & Katt, Basel (2020). Smart Policing for a Smart World Opportunities, Challenges and Way Forward. Advances in Intelligent Systems and Computing. ISSN 2194-5357. p {0}. doi: 10.1007/978-3-030-39445-5_39FULLTEKST
- Alazab, Moutaz, Alazab, Mamoun, Shalaginov, Andrii, Mesleh, Abdelwadood & Awajan, Albara (2020). Intelligent mobile malware detection using permission requests and API calls. Future Generation Computer Systems. ISSN 0167-739X. 107 p {0}. doi: 10.1016/j.future.2020.02.002
- Michailidou, Christina, Gkioulos, Vasileios, Shalaginov, Andrii, Rizos, Athanasios & Saracino, Andrea (2020). RESPOnSE—A Framework for Enforcing Risk-Aware Security Policies in Constrained Dynamic Environments . Sensors. ISSN 1424-8220. 20(10) doi: 10.3390/s20102960
- Azad, Muhammad Ajmal, Bag, Samiran, Feng, Hao & Shalaginov, Andrii (2020). Decentralized Self-Enforcing Trust Management System for Social Internet of Things. IEEE Internet of Things Journal. ISSN 2327-4662. 7(4) p {0}. doi: 10.1109/JIOT.2019.2962282
- Kumar, Ajit, Agarwal, Vinti, Kumar Shandilya, Shishir, Shalaginov, Andrii, Upadhyay, Saket & Yadav, Bhawna (2020). PACER: Platform for Android Malware Classification, Performance Evaluation and Threat Reporting. Future Internet. ISSN 1999-5903. 12(4) doi: 10.3390/fi12040066
- Shalaginov, Andrii, Iqbal, Asif & Olegård, Johannes (2020). IoT Digital Forensics Readiness in the Edge: A Roadmap for Acquiring Digital Evidences from Intelligent Smart Applications. I Katangur, Ajay, Lin, Shih-Chun, Wei, Jinpeng, Yang, Shuhui & Zhang, Liang-Jie (red.) Edge Computing – EDGE 2020. Springer. ISBN 978-3-030-59823-5. doi: 10.1007/978-3-030-59824-2_1
- Gunleifsen, Håkon, Gkioulos, Vasileios, Wangen, Gaute, Shalaginov, Andrii, Kianpour, Mazaher & Abomhara, Mohamed Ali Saleh (2019). Cybersecurity Awareness and Culture in Rural Norway. I Furnell, Steven & Clarke, Nathan (red.) Thirteenth International Symposium on Human Aspects of Information Security & Assurance (HAISA 2019). University of Plymouth Press. ISBN 978-0244-19096-5. p {0}. FULLTEKST
- Shalaginov, Andrii, Semeniuta, Oleksandr & Alazab, Mamoun (2019). MEML: Resource-aware MQTT-based Machine Learning for Network Attacks Detection on IoT Edge Devices. I Johnson, Kenneth & Spillner, Josef (red.) Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Companion. Association for Computing Machinery (ACM). ISBN 978-1-4503-7044-8. p {0}. doi: 10.1145/3368235.3368876
- Faiz, Mohamed Falah, Arshad, Junaid, Alazab, Mamoun & Shalaginov, Andrii (2019). Predicting likelihood of legitimate data loss in email DLP. Future Generation Computer Systems. ISSN 0167-739X. doi: 10.1016/j.future.2019.11.004
- Kumar, Ajit, Agarwal, Vinti, Shandilya, Shishir K., Shalaginov, Andrii, Upadhyay, Saket & Yadav, Bhawna (2019). PACE: Platform for Android Malware Classification and Performance Evaluation. I IEEE, . (red.) 2019 IEEE International Conference on Big Data (Big Data). IEEE (Institute of Electrical and Electronics Engineers). ISBN 978-1-7281-0858-2.
- Shalaginov, Andrii (2018). Advancing Neuro-Fuzzy Algorithm for Automated Classification in Large-scale Forensic and Cybercrime Investigations: Adaptive Machine Learning for Big Data Forensic. Norges teknisk-naturvitenskapelige universitet. ISBN 978-82-326-2906-0. 2018(57)
- Shalaginov, Andrii, Banin, Sergii, Dehghantanha, Ali & Franke, Katrin (2018). Machine Learning Aided Static Malware Analysis: A Survey and Tutorial. I Dehghantanha, Ali, Conti, Mauro & Dargahi, Tooska (red.) Cyber Threat Intelligence. Springer. ISBN 978-3-319-73951-9. p {0}. doi: 10.1007/978-3-319-73951-9_2FULLTEKST
- Iqbal, Asif, Mahmood, Farhan, Shalaginov, Andrii & Ekstedt, Mathias (2018). Identification of Attack-based Digital Forensic Evidences for WAMPAC Systems. I Abe, Naoki, Liu, Huan, Hu, Xiaohua, Ahmed, Nesreen, Qiao, Mu, Song, Yang, Kossmann, Donald, Liu, Bing, Lee, Kisung, Tang, Jiliang, He, Jingrui & Saltz, Jeffrey (red.) 2018 IEEE International Conference on Big Data (Big Data), Seattle, 10-13 Dec. 2018. IEEE (Institute of Electrical and Electronics Engineers). ISBN 978-1-5386-5035-6. p {0}. doi: 10.1109/BigData.2018.8622550
- Iqbal, Asif, Shalaginov, Andrii & Mahmood, Farhan (2018). Intelligent analysis of digital evidences in large-scale logs in power systems attributed to the attacks. I Abe, Naoki, Liu, Huan, Hu, Xiaohua, Ahmed, Nesreen, Qiao, Mu, Song, Yang, Kossmann, Donald, Liu, Bing, Lee, Kisung, Tang, Jiliang, He, Jingrui & Saltz, Jeffrey (red.) 2018 IEEE International Conference on Big Data (Big Data), Seattle, 10-13 Dec. 2018. IEEE (Institute of Electrical and Electronics Engineers). ISBN 978-1-5386-5035-6. p {0}. doi: 10.1109/BigData.2018.8622220
- Hansen, Joachim, Porter, Kyle, Shalaginov, Andrii & Franke, Katrin (2018). Comparing Open Source Search Engine Functionality, Efficiency and Effectiveness with Respect to Digital Forensic Search . Norsk Informasjonssikkerhetskonferanse (NISK). ISSN 1893-6563. 11 FULLTEKST
- Shalaginov, Andrii & Franke, Katrin (2017). Big data analytics by automated generation of fuzzy rules for Network Forensics Readiness. Applied Soft Computing. ISSN 1568-4946. 52 p {0}. doi: 10.1016/j.asoc.2016.10.029
- Shalaginov, Andrii (2017). Dynamic feature-based expansion of fuzzy sets in Neuro-Fuzzy for proactive malware detection. I IEEE, . (red.) 2017 20th International Conference on Information Fusion. IEEE (Institute of Electrical and Electronics Engineers). ISBN 978-0-9964-5270-0. p {0}. doi: 10.23919/ICIF.2017.8009812FULLTEKST
- Shalaginov, Andrii (2017). Evolutionary optimization of on-line multilayer perceptron for similarity-based access control. I Choe, Yoonsuck (red.) 2017 International Joint Conference on Neural Networks (IJCNN). IEEE (Institute of Electrical and Electronics Engineers). ISBN 978-1-5090-6182-2. p {0}. doi: 10.1109/IJCNN.2017.7965937FULLTEKST
- Shalaginov, Andrii (2017). Fuzzy logic model for digital forensics: A trade-off between accuracy, complexity and interpretability. IJCAI International Joint Conference on Artificial Intelligence. ISSN 1045-0823. p {0}. doi: 10.24963/ijcai.2017/763FULLTEKST
- Shalaginov, Andrii, Franke, Katrin & Johnsen, Jan William (2017). IEEE Big Data 1st International Workshop on Big Data Analytic for Cyber Crime Investigation and Prevention 2017. IEEE (Institute of Electrical and Electronics Engineers). ISBN 978-1-5386-2715-0. FULLTEKST
- Shalaginov, Andrii, Johnsen, Jan William & Franke, Katrin (2017). Cyber crime investigations in the era of big data. I Shalaginov, Andrii, Franke, Katrin & Johnsen, Jan William (red.) IEEE Big Data 1st International Workshop on Big Data Analytic for Cyber Crime Investigation and Prevention 2017. IEEE (Institute of Electrical and Electronics Engineers). ISBN 978-1-5386-2715-0. p {0}. doi: 10.1109/BigData.2017.8258362
- Shalaginov, Andrii & Franke, Katrin (2017). A Deep Neuro-Fuzzy method for multi-label malware classification and fuzzy rules extraction. I Bonissone, Piero & Fogel, David (red.) 2017 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings. IEEE (Institute of Electrical and Electronics Engineers). ISBN 978-1-5386-2726-6. p {0}. doi: 10.1109/SSCI.2017.8280788
- Wangen, Gaute & Shalaginov, Andrii (2016). Quantitative Risk, Statistical Methods and the Four Quadrants for Information Security. I Lambrinoudakis, Costas & Gabillon, Alban (red.) Risks and Security of Internet and Systems: 10th International Conference, CRiSIS 2015, Mytilene, Lesbos Island, Greece, July 20-22, 2015, Revised Selected Papers. Springer. ISBN 978-3-319-31811-0. p {0}. doi: 10.1007/978-3-319-31811-0_8
- Shalaginov, Andrii & Franke, Katrin (2016). Multinomial classification of web attacks using improved fuzzy rules learning by Neuro-Fuzzy. International Journal of Hybrid Intelligent Systems. ISSN 1448-5869. 13(1) p {0}. doi: 10.3233/HIS-160221
- Shalaginov, Andrii, Franke, Katrin & Huang, Xiongwei (2016). Malware Beaconing Detection by Mining Large-scale DNS Logs for Targeted Attack Identification. International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering. ISSN 2010-376X. 10(4) p {0}. FULLTEKST
- Shalaginov, Andrii, Grini, Lars Strande & Franke, Katrin (2016). Understanding Neuro-Fuzzy on a Class of Multinomial Malware Detection Problems. I Estevez, Pablo A. (red.) IEEE International Joint Conference on Neural Networks (IJCNN). Research Publishing Services. ISBN 978-1-5090-0619-9. p {0}. doi: 10.1109/IJCNN.2016.7727266
- Shalaginov, Andrii (2016). Soft Computing and Hybrid Intelligence for Decision Support in Forensics Science. I Wang, Alan (red.) IEEE International Conference on Intelligence and
Security Informatics: Cybersecurity and Big Data. IEEE (Institute of Electrical and Electronics Engineers). ISBN 978-1-5090-3865-7. p {0}. doi: 10.1109/ISI.2016.7745495
- Wangen, Gaute, Shalaginov, Andrii & Hallstensen, Christoffer V (2016). Cyber security risk assessment of a DDoS attack. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 9866 p {0}. doi: 10.1007/978-3-319-45871-7_12
- Andersen, Lars Christian, Franke, Katrin & Shalaginov, Andrii (2016). Data-driven Approach to Information Sharing using Data Fusion and Machine Learning for Intrusion Detection. Norsk Informasjonssikkerhetskonferanse (NISK). ISSN 1893-6563. 2016 p {0}. FULLTEKST
- Banin, Sergii, Shalaginov, Andrii & Franke, Katrin (2016). Memory access patterns for malware detection. Norsk Informasjonssikkerhetskonferanse (NISK). ISSN 1893-6563. 2016 p {0}. FULLTEKST
- Shalaginov, Andrii & Franke, Katrin (2016). Intelligent generation of fuzzy rules for network firewalls based on the analysis of large-scale network traffic dumps. International Journal of Hybrid Intelligent Systems. ISSN 1448-5869. 13(3-4) p {0}. doi: 10.3233/HIS-170236FULLTEKST
- Shalaginov, Andrii & Franke, Katrin (2015). A New Method for an Optimal SOM Size Determination in Neuro-Fuzzy for the Digital Forensics Applications. I Rojas, Ignacio, Joya, Gonzalo & Catala, Andreu (red.) Advances in Computational Intelligence; 13th International Work-Conference on Artificial Neural Networks, IWANN 2015, Palma de Mallorca, Spain, June 10-12, 2015. Proceedings, Part II. Springer. ISBN 978-3-319-19222-2. p {0}. doi: 10.1007/978-3-319-19222-2_46
- Shalaginov, Andrii & Franke, Katrin (2015). A new method of fuzzy patches construction in Neuro-Fuzzy for malware detection. I Alonso, José M., Bustince, Humberto & Reformat, Marek (red.) Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology, Eusflat-15. Atlantis Press. ISBN 978-94-62520-77-6. p {0}. doi: 10.2991/ifsa-eusflat-15.2015.27
- Shalaginov, Andrii & Franke, Katrin (2015). Towards Improvement of Multinomial Classification Accuracy of Neuro-Fuzzy for Digital Forensics Applications. I Abraham, Ajith, Yong Han, Sang, Al-Sharhan, Salah A. & Liu, Hongbo (red.) Hybrid Intelligent Systems - proceedings of 15th International Conference HIS 2015 on Hybrid Intelligent Systems. Springer Publishing Company. ISBN 978-3-319-27220-7. p {0}. doi: 10.1007/978-3-319-27221-4_17
- Shalaginov, Andrii & Franke, Katrin (2015). Automated generation of fuzzy rules from large-scale network traffic analysis in Digital Forensics Investigations. I Köppen, Mario, Xue, Bing, Takagi, Hideyuki, Abraham, Ajith, Muda, Azah Kamilah & Ma, Kun (red.) 2015 Seventh International Conference of Soft Computing and Pattern Recognition (SoCPaR 2015). IEEE (Institute of Electrical and Electronics Engineers). ISBN 978-1-4673-9360-7. p {0}. doi: 10.1109/socpar.2015.7492778
- Shalaginov, Andrii & Franke, Katrin (2013). Automatic rule-mining for malware detection employing Neuro-Fuzzy Approach. I Rong, Chunming & Oleshchuk, Vladimir (red.) Proceeding of Norwegian Information Security Conference / Norsk informasjonssikkerhetskonferanse - NISK 2013 - Stavanger, 18th-20th November 2013. Akademika forlag. ISBN 978-82-321-0366-9. p {0}. doi: 10.2991/ifsa-eusflat-15.2015.27
Dissemination
- Shalaginov, Andrii (2023). Artificial Intelligence for Cybersecurity in Resource-Constrained Smart Infrastructures: Applicability, Opportunities and Energy Modelling.
- Shalaginov, Andrii (2023). Panel Session on "The Impact of Artificial Intelligence on Enforcement Activities".
- Shalaginov, Andrii (2023). AI for Cybersecurity in Resource-Constrained Smart Infrastructures.
- Shalaginov, Andrii (2022). Cybersecurity in smart grid system.
- Shalaginov, Andrii (2022). The 6th International Workshop on Big Data Analytic for Cyber Crime Investigation and Prevention 2022.
- Shalaginov, Andrii (2022). Building AI-based middleware for cyber attacks detection in the next generation Smart Environments.
- Shalaginov, Andrii (2022). Artificial Intelligence for Cybersecurity in Resource-Constrained Smart Infrastructures: Applicability, Opportunities and Energy Modelling .
- Shalaginov, Andrii (2022). EU-prosjekt ENViSEC .
- Bhandari, Guru, Lyth, Andreas, Shalaginov, Andrii & Grønli, Tor-Morten (2022). Artificial Intelligence Enabled Middleware for Distributed Cyberattacks Detection in IoT-based Smart Environments. FULLTEKST
- Shalaginov, Andrii (2021). Digital Evidences Analysis of embedded devices and IoT Forensics .
- Shalaginov, Andrii & Grønli, Tor-Morten (2021). ENViSEC: Artificial Intelligence- enabled Cybersecurity for Future Smart Environments.
- Shalaginov, Andrii (2021). Artificial Intelligence and New Technologies.
- Shalaginov, Andrii (2021). The 5th International Workshop on Big Data Analytic for Cyber Crime Investigation and Prevention 2021.
- Shalaginov, Andrii & Grønli, Tor-Morten (2021). Workshop on Building Next Generation Internet: Artificial Intelligence-enabled Cybersecurity for IoT in Future Smart Environments.
- Shalaginov, Andrii (2021). ENViSEC project: Securing Smart Future.
- Shalaginov, Andrii (2021). AI-based cybersecurity research at Høyskolen Kristiania.
- Shalaginov, Andrii (2020). Identification and analysis of malware on selected suspected copyright-infringing websites .
- Shalaginov, Andrii (2019). Life after Ph.D: collaboration, networking and funding opportunities.
- Shalaginov, Andrii (2019). Digital Footprint and Cybersecurity.
- Shalaginov, Andrii, Franke, Katrin & Johnsen, Jan William (2018). The 2nd International Workshop on Big Data Analytic for Cyber Crime Investigation and Prevention 2018. FULLTEKST
- Shalaginov, Andrii (2017). Machine Learning Aided Malware Analysis - Research at NTNU.
- Shalaginov, Andrii (2017). Computational Forensics .
- Shalaginov, Andrii (2015). Automated generation of the human-understandable rules from network traffic dumps.
- Shalaginov, Andrii (2015). Application of Computational Intelligence for Digital Forensics.
- Shalaginov, Andrii & Franke, Katrin (2015). Generation of the human-understandable fuzzy rules from large-scale datasets for Digital Forensics applications using Neuro-Fuzzy.