Andrii Shalaginov
Andrii Shalaginov
Kristiania University College
Verified email at - Homepage
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
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
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
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
Big data analytics by automated generation of fuzzy rules for Network Forensics Readiness
A Shalaginov, K Franke
Applied Soft Computing 52, 359-375, 2017
A new method of fuzzy patches construction in Neuro-Fuzzy for malware detection
A Shalaginov, K Franke
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
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
Automated intelligent multinomial classification of malware species using dynamic behavioural analysis
A Shalaginov, K Franke
IEEE Privacy, Security and Trust 2016, 2016
Automatic rule-mining for malware detection employing neuro-fuzzy approach
A Shalaginov, K Franke
Norsk informasjonssikkerhetskonferanse (NISK) 2013, 2013
Cyber security risk assessment of a ddos attack
G Wangen, A Shalaginov, C Hallstensen
International Conference on Information Security, 183-202, 2016
Memory access patterns for malware detection
S Banin, A Shalaginov, K Franke
NISK, 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
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
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
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
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