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Andrii Shalaginov
Andrii Shalaginov
Kristiania University College
Verified email at kristiania.no - Homepage
Title
Cited by
Cited by
Year
Intelligent mobile malware detection using permission requests and API calls
M Alazab, M Alazab, A Shalaginov, A Mesleh, A Awajan
Future Generation Computer Systems 107, 509-521, 2020
2202020
Machine learning aided static malware analysis: A survey and tutorial
A Shalaginov, S Banin, A Dehghantanha, K Franke
Cyber threat intelligence, 7-45, 2018
1312018
Deep graph neural network-based spammer detection under the perspective of heterogeneous cyberspace
Z Guo, L Tang, T Guo, K Yu, M Alazab, A Shalaginov
Future generation computer systems 117, 205-218, 2021
1252021
Decentralized self-enforcing trust management system for social Internet of Things
MA Azad, S Bag, F Hao, A Shalaginov
IEEE Internet of Things Journal 7 (4), 2690-2703, 2020
732020
BCFL logging: An approach to acquire and preserve admissible digital forensics evidence in cloud ecosystem
K Awuson-David, T Al-Hadhrami, M Alazab, N Shah, A Shalaginov
Future Generation Computer Systems 122, 1-13, 2021
462021
Cyber crime investigations in the era of big data
A Shalaginov, JW Johnsen, K Franke
2017 IEEE International Conference on Big Data (Big Data), 3672-3676, 2017
342017
A new method for an optimal som size determination in neuro-fuzzy for the digital forensics applications
A Shalaginov, K Franke
International Work-Conference on Artificial Neural Networks, 549-563, 2015
312015
Big data analytics by automated generation of fuzzy rules for Network Forensics Readiness
A Shalaginov, K Franke
Applied Soft Computing 52, 359-375, 2017
252017
Understanding Neuro-Fuzzy on a class of multinomial malware detection problems
A Shalaginov, LS Grini, K Franke
International Joint Conference on Neural Networks (IJCNN) 2016, 684-691, 2016
252016
Malware Analysis Using Artificial Intelligence and Deep Learning
M Stamp, M Alazab, A Shalaginov
Springer Nature, 2020
242020
MEML: Resource-aware MQTT-based machine learning for network attacks detection on IoT edge devices
A Shalaginov, O Semeniuta, M Alazab
Proceedings of the 12th IEEE/ACM International Conference on Utility and …, 2019
232019
Malware Beaconing Detection by Mining Large-scale DNS Logs for Targeted Attack Identification
A Shalaginov, K Franke, X Huang
18th International Conference on Computational Intelligence in Security …, 2016
232016
Predicting likelihood of legitimate data loss in email DLP
MF Faiz, J Arshad, M Alazab, A Shalaginov
Future Generation Computer Systems 110, 744-757, 2020
222020
Iot digital forensics readiness in the edge: A roadmap for acquiring digital evidences from intelligent smart applications
A Shalaginov, A Iqbal, J Olegård
Edge Computing–EDGE 2020: 4th International Conference, Held as Part of the …, 2020
202020
Distributed deep neural-network-based middleware for cyber-attacks detection in smart IoT ecosystem: a novel framework and performance evaluation approach
G Bhandari, A Lyth, A Shalaginov, TM Grønli
Electronics 12 (2), 298, 2023
182023
A new method of fuzzy patches construction in Neuro-Fuzzy for malware detection
A Shalaginov, K Franke
IFSA-EUSFLAT, 2015
182015
Memory access patterns for malware detection
S Banin, A Shalaginov, K Franke
NISK, 2016
172016
Study of Soft Computing methods for large-scale multinomial malware types and families detection
LS Grini, A Shalaginov, K Franke
The 6th World Conference on Soft Computing, 2016
172016
A novel architectural framework on IoT ecosystem, security aspects and mechanisms: a comprehensive survey
M Bouzidi, N Gupta, FA Cheikh, A Shalaginov, M Derawi
IEEE Access 10, 101362-101384, 2022
162022
Smart home forensics: An exploratory study on smart plug forensic analysis
A Iqbal, J Olegård, R Ghimire, S Jamshir, A Shalaginov
2020 IEEE International Conference on Big Data (Big Data), 2283-2290, 2020
162020
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