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1 Shalaginov, Andrii.
Identification and analysis of malware on selected suspected copyright-infringing websites. Observatory Impact of Technology Expert Group Meeting; 2020-01-30 - 2020-01-31
NTNU Untitled
2 Yamin, Muhammad Mudassar; Shalaginov, Andrii; Katt, Basel.
Smart Policing for a Smart World Opportunities, Challenges and Way Forward. Advances in Intelligent Systems and Computing 2020 s. 532-549
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3 Faiz, Mohamed Falah; Arshad, Junaid; Alazab, Mamoun; Shalaginov, Andrii.
Predicting likelihood of legitimate data loss in email DLP. Future generations computer systems 2019 s. -
NTNU Untitled
4 Gunleifsen, Håkon; Gkioulos, Vasileios; Wangen, Gaute; Shalaginov, Andrii; Kianpour, Mazaher; Abomhara, Mohamed Ali Saleh.
Cybersecurity Awareness and Culture in Rural Norway. I: Thirteenth International Symposium on Human Aspects of Information Security & Assurance (HAISA 2019). University of Plymouth Press 2019 ISBN 978-0244-19096-5. s. 110-121
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5 Shalaginov, Andrii.
Digital Footprint and Cybersecurity. Gjøvikregionen International School - guest lecture; 2019-11-13 - 2019-11-13
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6 Shalaginov, Andrii.
Life after Ph.D: collaboration, networking and funding opportunities. COINS PhD Seminar 2019; 2019-11-25 - 2019-11-25
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7 Shalaginov, Andrii; Semeniuta, Oleksandr; Alazab, Mamoun.
MEML: Resource-aware MQTT-based Machine Learning for Network Attacks Detection on IoT Edge Devices. I: Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Companion. Association for Computing Machinery (ACM) 2019 ISBN 978-1-4503-7044-8. s. 123-128
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8 Hansen, Joachim; Porter, Kyle; Shalaginov, Andrii; Franke, Katrin.
Comparing Open Source Search Engine Functionality, Efficiency and Effectiveness with Respect to Digital Forensic Search. Norsk Informasjonssikkerhetskonferanse (NISK) 2018 ;Volum 11.
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9 Iqbal, Asif; Mahmood, Farhan; Shalaginov, Andrii; Ekstedt, Mathias.
Identification of Attack-based Digital Forensic Evidences for WAMPAC Systems. I: 2018 IEEE International Conference on Big Data (Big Data), Seattle, 10-13 Dec. 2018. IEEE 2018 ISBN 978-1-5386-5035-6. s. 3079-3087
NTNU Untitled
10 Iqbal, Asif; Shalaginov, Andrii; Mahmood, Farhan.
Intelligent analysis of digital evidences in large-scale logs in power systems attributed to the attacks. I: 2018 IEEE International Conference on Big Data (Big Data), Seattle, 10-13 Dec. 2018. IEEE 2018 ISBN 978-1-5386-5035-6. s. 3088-3093
NTNU Untitled
11 Shalaginov, Andrii.
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 2018 (ISBN 978-82-326-2906-0) ;Volum 2018.349 s. Doktoravhandlinger ved NTNU(57)
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12 Shalaginov, Andrii; Banin, Sergii; Dehghantanha, Ali; Franke, Katrin.
Machine Learning Aided Static Malware Analysis: A Survey and Tutorial. I: Cyber Threat Intelligence. Springer 2018 ISBN 978-3-319-73951-9. s. 7-45
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13 Shalaginov, Andrii; Franke, Katrin; Johnsen, Jan William.
The 2nd International Workshop on Big Data Analytic for Cyber Crime Investigation and Prevention 2018. IEEE International Conference on Big Data 2018; 2018-12-10 - 2018-12-13
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14 Shalaginov, Andrii.
Computational Forensics. IEEE Big Data 1st International Workshop on Big Data Analytic for Cyber Crime Investigation and Prevention; 2017-12-11 - 2017-12-11
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15 Shalaginov, Andrii.
Dynamic feature-based expansion of fuzzy sets in Neuro-Fuzzy for proactive malware detection. I: 2017 20th International Conference on Information Fusion. IEEE 2017 ISBN 978-0-9964-5270-0. s. 1-8
NTNU Untitled
16 Shalaginov, Andrii.
Evolutionary optimization of on-line multilayer perceptron for similarity-based access control. I: 2017 International Joint Conference on Neural Networks (IJCNN). IEEE 2017 ISBN 978-1-5090-6182-2. s. 823-830
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17 Shalaginov, Andrii.
Fuzzy logic model for digital forensics: A trade-off between accuracy, complexity and interpretability. IJCAI International Joint Conference on Artificial Intelligence 2017 s. 5207-5208
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18 Shalaginov, Andrii.
Machine Learning Aided Malware Analysis - Research at NTNU. NorCERT sikkerhetsforum; 2017-03-30 - 2017-03-30
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19 Shalaginov, Andrii; Franke, Katrin.
A Deep Neuro-Fuzzy method for multi-label malware classification and fuzzy rules extraction. I: 2017 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings. IEEE 2017 ISBN 978-1-5386-2726-6. s. 533-540
NTNU Untitled
20 Shalaginov, Andrii; Franke, Katrin.
Big data analytics by automated generation of fuzzy rules for Network Forensics Readiness. Applied Soft Computing 2017 ;Volum 52. s. 359-375
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21 Shalaginov, Andrii; Franke, Katrin; Johnsen, Jan William.
IEEE Big Data 1st International Workshop on Big Data Analytic for Cyber Crime Investigation and Prevention 2017. IEEE 2017 (ISBN 978-1-5386-2715-0)
NTNU UiO Untitled
22 Shalaginov, Andrii; Johnsen, Jan William; Franke, Katrin.
Cyber Crime Investigations in the Era of Big Data. I: IEEE Big Data 1st International Workshop on Big Data Analytic for Cyber Crime Investigation and Prevention 2017. IEEE 2017 ISBN 978-1-5386-2715-0. s. 3672-3676
NTNU Untitled
23 Andersen, Lars Christian; Franke, Katrin; Shalaginov, Andrii.
Data-driven Approach to Information Sharing using Data Fusion and Machine Learning for Intrusion Detection. Norsk Informasjonssikkerhetskonferanse (NISK) 2016 ;Volum 2016. s. 19-30
NTNU Untitled
24 Banin, Sergii; Shalaginov, Andrii; Franke, Katrin.
Memory access patterns for malware detection. Norsk Informasjonssikkerhetskonferanse (NISK) 2016 ;Volum 2016. s. 96-107
NTNU Untitled
25 Shalaginov, Andrii.
Soft Computing and Hybrid Intelligence for Decision Support in Forensics Science. I: IEEE International Conference on Intelligence and Security Informatics: Cybersecurity and Big Data. IEEE 2016 ISBN 978-1-5090-3865-7. s. 304-306
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26 Shalaginov, Andrii; Franke, Katrin.
Intelligent generation of fuzzy rules for network firewalls based on the analysis of large-scale network traffic dumps. International Journal of Hybrid Intelligent Systems 2016 ;Volum 13.(3-4) s. 195-206
NTNU Untitled
27 Shalaginov, Andrii; Franke, Katrin.
Multinomial classification of web attacks using improved fuzzy rules learning by Neuro-Fuzzy. International Journal of Hybrid Intelligent Systems 2016 ;Volum 13.(1) s. 15-26
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28 Shalaginov, Andrii; Franke, Katrin; Huang, Xiongwei.
Malware Beaconing Detection by Mining Large-scale DNS Logs for Targeted Attack Identification. International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering 2016 ;Volum 10.(4) s. 617-629
NTNU Untitled
29 Shalaginov, Andrii; Grini, Lars Strande; Franke, Katrin.
Understanding Neuro-Fuzzy on a Class of Multinomial Malware Detection Problems. I: IEEE International Joint Conference on Neural Networks (IJCNN). Research Publishing Services 2016 ISBN 978-1-5090-0619-9. s. 684-691
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30 Wangen, Gaute; Shalaginov, Andrii.
Quantitative Risk, Statistical Methods and the Four Quadrants for Information Security. I: Risks and Security of Internet and Systems: 10th International Conference, CRiSIS 2015, Mytilene, Lesbos Island, Greece, July 20-22, 2015, Revised Selected Papers. Springer 2016 ISBN 978-3-319-31811-0. s. 127-143
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31 Wangen, Gaute; Shalaginov, Andrii; Hallstensen, Christoffer V.
Cyber security risk assessment of a DDoS attack. Lecture Notes in Computer Science (LNCS) 2016 ;Volum 9866. s. 183-202
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32 Shalaginov, Andrii.
Application of Computational Intelligence for Digital Forensics. COINS PhD Seminar; 2015-10-18 - 2015-10-19
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33 Shalaginov, Andrii.
Automated generation of the human-understandable rules from network traffic dumps. 3rd National Workshop on Data Science ( SweDS ); 2015-09-30 - 2015-10-01
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34 Shalaginov, Andrii; Franke, Katrin.
A New Method for an Optimal SOM Size Determination in Neuro-Fuzzy for the Digital Forensics Applications. I: 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 2015 ISBN 978-3-319-19222-2. s. 549-563
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35 Shalaginov, Andrii; Franke, Katrin.
A new method of fuzzy patches construction in Neuro-Fuzzy for malware detection. I: Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology, Eusflat-15. Atlantis Press 2015 ISBN 978-94-62520-77-6. s. 170-177
NTNU Untitled
36 Shalaginov, Andrii; Franke, Katrin.
Automated generation of fuzzy rules from large-scale network traffic analysis in Digital Forensics Investigations. I: 2015 Seventh International Conference of Soft Computing and Pattern Recognition (SoCPaR 2015). IEEE 2015 ISBN 978-1-4673-9360-7. s. 31-36
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37 Shalaginov, Andrii; Franke, Katrin.
Generation of the human-understandable fuzzy rules from large-scale datasets for Digital Forensics applications using Neuro-Fuzzy. NordSec; 2015-10-19 - 2015-10-21
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38 Shalaginov, Andrii; Franke, Katrin.
Towards Improvement of Multinomial Classification Accuracy of Neuro-Fuzzy for Digital Forensics Applications. I: Hybrid Intelligent Systems - proceedings of 15th International Conference HIS 2015 on Hybrid Intelligent Systems. Springer Publishing Company 2015 ISBN 978-3-319-27220-7. s. 199-210
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39 Shalaginov, Andrii; Franke, Katrin.
Automatic rule-mining for malware detection employing Neuro-Fuzzy Approach. I: Proceeding of Norwegian Information Security Conference / Norsk informasjonssikkerhetskonferanse - NISK 2013 - Stavanger, 18th-20th November 2013. Akademika forlag 2013 ISBN 978-82-321-0366-9. s. 100-111
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