Andrii Shalaginov
Andrii Shalaginov
Kristiania University College
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Cited by
Cited by
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
Machine learning aided static malware analysis: A survey and tutorial
A Shalaginov, S Banin, A Dehghantanha, K Franke
Cyber threat intelligence, 7-45, 2018
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
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
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
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
A new method of fuzzy patches construction in Neuro-Fuzzy for malware detection
A Shalaginov, K Franke
Big data analytics by automated generation of fuzzy rules for Network Forensics Readiness
A Shalaginov, K Franke
Applied Soft Computing 52, 359-375, 2017
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
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
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
Automatic rule-mining for malware detection employing neuro-fuzzy approach
A Shalaginov, K Franke
Norsk informasjonssikkerhetskonferanse (NISK) 2013, 2013
Automated intelligent multinomial classification of malware species using dynamic behavioural analysis
A Shalaginov, K Franke
IEEE Privacy, Security and Trust 2016, 2016
Towards improvement of multinomial classification accuracy of Neuro-Fuzzy for Digital Forensics applications
A Shalaginov, K Franke
15th International Conference on Hybrid Intelligent Systems (HIS 2015) 420 …, 2015
Cyber security risk assessment of a ddos attack
G Wangen, A Shalaginov, C Hallstensen
International Conference on Information Security, 183-202, 2016
Automated Generation of Fuzzy Rules from Large-scale Network Traffic Analysis in Digital Forensics Investigations
A Shalaginov, K Franke
7th International Conference on Soft Computing and Pattern Recognition …, 2015
Multinomial classification of web attacks using improved fuzzy rules learning by neuro-fuzzy
A Shalaginov, K Franke
International Journal of Hybrid Intelligent Systems 13 (1), 15-26, 2016
Advancing Neuro-Fuzzy Algorithm for Automated Classification in Largescale Forensic and Cybercrime Investigations: Adaptive Machine Learning for Big Data Forensic
A Shalaginov
Norwegian University of Science and Technology, 2018
Memory access patterns for malware detection
S Banin, A Shalaginov, K Franke
NISK, 2016
Soft Computing and Hybrid Intelligence for Decision Support in Forensics Science
A Shalaginov
IEEE Intelligence and Security Informatics 2016, 304-309, 2016
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