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Andrii Shalaginov
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2020 – today
- 2024
- [j16]Guru Prasad Bhandari, Gebremariam Assres, Nikola Gavric, Andrii Shalaginov, Tor-Morten Grønli:
IoTvulCode: AI-enabled vulnerability detection in software products designed for IoT applications. Int. J. Inf. Sec. 23(4): 2677-2690 (2024) - [j15]Nikola Gavric, Guru Prasad Bhandari, Andrii Shalaginov:
Towards Resource-Efficient DDoS Detection in IoT: Leveraging Feature Engineering of System and Network Usage Metrics. J. Netw. Syst. Manag. 32(4): 69 (2024) - 2023
- [j14]Karl Edvard Balto, Muhammad Mudassar Yamin
, Andrii Shalaginov, Basel Katt
:
Hybrid IoT Cyber Range. Sensors 23(6): 3071 (2023) - 2022
- [j13]Mohammed Bouzidi
, Nishu Gupta
, Faouzi Alaya Cheikh
, Andrii Shalaginov
, Mohammad Omar Derawi
:
A Novel Architectural Framework on IoT Ecosystem, Security Aspects and Mechanisms: A Comprehensive Survey. IEEE Access 10: 101362-101384 (2022) - [c26]Guru Prasad Bhandari, Andreas Lyth, Andrii Shalaginov, Tor-Morten Grønli:
Artificial Intelligence Enabled Middleware for Distributed Cyberattacks Detection in IoT-based Smart Environments. IEEE Big Data 2022: 3023-3032 - 2021
- [j12]Zhiwei Guo
, Lianggui Tang, Tan Guo, Keping Yu
, Mamoun Alazab
, Andrii Shalaginov:
Deep Graph neural network-based spammer detection under the perspective of heterogeneous cyberspace. Future Gener. Comput. Syst. 117: 205-218 (2021) - [j11]Kenny Awuson-David
, Tawfik Al Hadhrami
, Mamoun Alazab
, Nazaraf Shah
, Andrii Shalaginov:
BCFL logging: An approach to acquire and preserve admissible digital forensics evidence in cloud ecosystem. Future Gener. Comput. Syst. 122: 1-13 (2021) - [j10]Andrii Shalaginov
, Muhammad Ajmal Azad
:
Securing Resource-Constrained IoT Nodes: Towards Intelligent Microcontroller-Based Attack Detection in Distributed Smart Applications. Future Internet 13(11): 272 (2021) - [c25]Andrii Shalaginov, Tor-Morten Grønli:
Securing Smart Future: Cyber Threats and Intelligent Means to Respond. IEEE BigData 2021: 2560-2564 - 2020
- [j9]Moutaz Alazab
, Mamoun Alazab
, Andrii Shalaginov, Abdelwadood Mesleh, Albara W. Awajan
:
Intelligent mobile malware detection using permission requests and API calls. Future Gener. Comput. Syst. 107: 509-521 (2020) - [j8]Andrii Shalaginov:
Big Data Analytics and Artificial Intelligence for Cyber Crime Investigation and Prevention. Future Gener. Comput. Syst. 109: 702-703 (2020) - [j7]Mohamed Falah Faiz, Junaid Arshad, Mamoun Alazab
, Andrii Shalaginov:
Predicting likelihood of legitimate data loss in email DLP. Future Gener. Comput. Syst. 110: 744-757 (2020) - [j6]Ajit Kumar
, Vinti Agarwal, Shishir K. Shandilya
, Andrii Shalaginov, Saket Upadhyay
, Bhawna Yadav:
PACER: Platform for Android Malware Classification, Performance Evaluation and Threat Reporting. Future Internet 12(4): 66 (2020) - [j5]Muhammad Ajmal Azad
, Samiran Bag
, Feng Hao
, Andrii Shalaginov:
Decentralized Self-Enforcing Trust Management System for Social Internet of Things. IEEE Internet Things J. 7(4): 2690-2703 (2020) - [j4]Christina Michailidou
, Vasileios Gkioulos, Andrii Shalaginov, Athanasios Rizos
, Andrea Saracino
:
RESPOnSE - A Framework for Enforcing Risk-Aware Security Policies in Constrained Dynamic Environments. Sensors 20(10): 2960 (2020) - [c24]Asif Iqbal, Johannes Olegård
, Ranjana Ghimire, Shirin Jamshir, Andrii Shalaginov:
Smart Home Forensics: An Exploratory Study on Smart Plug Forensic Analysis. IEEE BigData 2020: 2283-2290 - [c23]Andrii Shalaginov, Marina Shalaginova, Aleksandar Jevremovic, Marko Krstic:
Modern Cybercrime Investigation: Technological Advancement of Smart Devices and Legal Aspects of Corresponding Digital Transformation. IEEE BigData 2020: 2328-2332 - [c22]Andrii Shalaginov, Asif Iqbal, Johannes Olegård
:
IoT Digital Forensics Readiness in the Edge: A Roadmap for Acquiring Digital Evidences from Intelligent Smart Applications. EDGE 2020: 1-17
2010 – 2019
- 2019
- [c21]Ajit Kumar, Vinti Agarwal, Shishir K. Shandilya
, Andrii Shalaginov, Saket Upadhyay
, Bhawna Yadav:
PACE: Platform for Android Malware Classification and Performance Evaluation. IEEE BigData 2019: 4280-4288 - [c20]Andrii Shalaginov, Igor Kotsiuba, Asif Iqbal:
Cybercrime Investigations in the Era of Smart Applications: Way Forward Through Big Data. IEEE BigData 2019: 4309-4314 - [c19]Håkon Gunleifsen, Vasileios Gkioulos, Gaute Wangen, Andrii Shalaginov, Mazaher Kianpour, Mohamed Abomhara:
Cybersecurity Awareness and Culture in Rural Norway. HAISA 2019: 110-121 - [c18]Andrii Shalaginov, Oleksandr Semeniuta, Mamoun Alazab
:
MEML: Resource-aware MQTT-based Machine Learning for Network Attacks Detection on IoT Edge Devices. UCC Companion 2019: 123-128 - 2018
- [c17]Asif Iqbal, Farhan Mahmood, Andrii Shalaginov, Mathias Ekstedt:
Identification of Attack-based Digital Forensic Evidences for WAMPAC Systems. IEEE BigData 2018: 3079-3087 - [c16]Asif Iqbal, Andrii Shalaginov, Farhan Mahmood:
Intelligent analysis of digital evidences in large-scale logs in power systems attributed to the attacks. IEEE BigData 2018: 3088-3093 - [i1]Andrii Shalaginov, Sergii Banin, Ali Dehghantanha, Katrin Franke:
Machine Learning Aided Static Malware Analysis: A Survey and Tutorial. CoRR abs/1808.01201 (2018) - 2017
- [j3]Andrii Shalaginov
, Katrin Franke
:
Big data analytics by automated generation of fuzzy rules for Network Forensics Readiness. Appl. Soft Comput. 52: 359-375 (2017) - [c15]Andrii Shalaginov, Jan William Johnsen, Katrin Franke:
Cyber crime investigations in the era of big data. IEEE BigData 2017: 3672-3676 - [c14]Andrii Shalaginov:
Dynamic feature-based expansion of fuzzy sets in Neuro-Fuzzy for proactive malware detection. FUSION 2017: 1-8 - [c13]Andrii Shalaginov:
Fuzzy Logic Model for Digital Forensics: A Trade-off between Accuracy, Complexity and Interpretability. IJCAI 2017: 5207-5208 - [c12]Andrii Shalaginov:
Evolutionary optimization of on-line multilayer perceptron for similarity-based access control. IJCNN 2017: 823-830 - [c11]Andrii Shalaginov, Katrin Franke:
A deep neuro-fuzzy method for multi-label malware classification and fuzzy rules extraction. SSCI 2017: 1-8 - 2016
- [j2]Andrii Shalaginov, Katrin Franke:
Multinomial classification of web attacks using improved fuzzy rules learning by Neuro-Fuzzy. Int. J. Hybrid Intell. Syst. 13(1): 15-26 (2016) - [j1]Andrii Shalaginov, Katrin Franke:
Intelligent generation of fuzzy rules for network firewalls based on the analysis of large-scale network traffic dumps. Int. J. Hybrid Intell. Syst. 13(3-4): 195-206 (2016) - [c10]Andrii Shalaginov, Lars Strande Grini, Katrin Franke:
Understanding Neuro-Fuzzy on a class of multinomial malware detection problems. IJCNN 2016: 684-691 - [c9]Andrii Shalaginov:
Soft Computing and Hybrid Intelligence for Decision Support in Forensics Science. ISI 2016: 304-306 - [c8]Gaute Wangen, Andrii Shalaginov, Christoffer Hallstensen:
Cyber Security Risk Assessment of a DDoS Attack. ISC 2016: 183-202 - [c7]Andrii Shalaginov, Katrin Franke:
Automated intelligent multinomial classification of malware species using dynamic behavioural analysis. PST 2016: 70-77 - [c6]Lars Strande Grini, Andrii Shalaginov, Katrin Franke:
Study of Soft Computing Methods for Large-Scale Multinomial Malware Types and Families Detection. WCSC 2016: 337-350 - 2015
- [c5]Gaute Wangen, Andrii Shalaginov:
Quantitative Risk, Statistical Methods and the Four Quadrants for Information Security. CRiSIS 2015: 127-143 - [c4]Andrii Shalaginov, Katrin Franke:
A new method of fuzzy patches construction in Neuro-Fuzzy for malware detection. IFSA-EUSFLAT 2015 - [c3]Andrii Shalaginov, Katrin Franke:
Towards Improvement of Multinomial Classification Accuracy of Neuro-Fuzzy for Digital Forensics Applications. HIS 2015: 199-210 - [c2]Andrii Shalaginov, Katrin Franke:
A New Method for an Optimal SOM Size Determination in Neuro-Fuzzy for the Digital Forensics Applications. IWANN (2) 2015: 549-563 - [c1]Andrii Shalaginov, Katrin Franke:
Automated generation of fuzzy rules from large-scale network traffic analysis in digital forensics investigations. SoCPaR 2015: 31-36
Coauthor Index
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last updated on 2024-08-13 20:49 CEST by the dblp team
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