Andrii Shalaginov

发表

Malware Beaconing Detection by Mining Large-scale DNS Logs for Targeted Attack Identification

Katrin Franke, Andrii Shalaginov, Xiongwei Huang, 2016 .

Machine Learning Aided Static Malware Analysis: A Survey and Tutorial pdf

Ali Dehghantanha, Katrin Franke, Sergii Banin, 2018, ArXiv.

Big Data Analytics and Artificial Intelligence for Cyber Crime Investigation and Prevention

Andrii Shalaginov, Andrii Shalaginov, 2020, Future Gener. Comput. Syst..

Cybercrime Investigations in the Era of Smart Applications: Way Forward Through Big Data

Andrii Shalaginov, Igor Kotsiuba, Asif Iqbal, 2019, 2019 IEEE International Conference on Big Data (Big Data).

Quantitative Risk, Statistical Methods and the Four Quadrants for Information Security

Andrii Shalaginov, Gaute Wangen, Andrii Shalaginov, 2015, CRiSIS.

Intelligent mobile malware detection using permission requests and API calls

Mamoun Alazab, Albara W. Awajan, Andrii Shalaginov, 2020, Future Gener. Comput. Syst..

A deep neuro-fuzzy method for multi-label malware classification and fuzzy rules extraction

Katrin Franke, Andrii Shalaginov, K. Franke, 2017, 2017 IEEE Symposium Series on Computational Intelligence (SSCI).

PACE: Platform for Android Malware Classification and Performance Evaluation

Andrii Shalaginov, Shishir K. Shandilya, Ajit Kumar, 2019, 2019 IEEE International Conference on Big Data (Big Data).

Predicting likelihood of legitimate data loss in email DLP

Junaid Arshad, Andrii Shalaginov, Mamoun Alazab, 2020, Future Gener. Comput. Syst..

Decentralized Self-Enforcing Trust Management System for Social Internet of Things

Muhammad Ajmal Azad, Andrii Shalaginov, Samiran Bag, 2020, IEEE Internet of Things Journal.

Cyber Security Risk Assessment of a DDoS Attack

Andrii Shalaginov, Gaute Wangen, Christoffer Hallstensen, 2016, ISC.

Understanding Neuro-Fuzzy on a class of multinomial malware detection problems

Katrin Franke, Andrii Shalaginov, Lars Strande Grini, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

A new method of fuzzy patches construction in Neuro-Fuzzy for malware detection

Katrin Franke, Andrii Shalaginov, K. Franke, 2015, IFSA-EUSFLAT.

Advancing Neuro-Fuzzy Algorithm for Automated Classification in Largescale Forensic and Cybercrime Investigations: Adaptive Machine Learning for Big Data Forensic

Andrii Shalaginov, Andrii Shalaginov, 2018 .

Dynamic feature-based expansion of fuzzy sets in Neuro-Fuzzy for proactive malware detection

Andrii Shalaginov, Andrii Shalaginov, 2017, 2017 20th International Conference on Information Fusion (Fusion).

Intelligent analysis of digital evidences in large-scale logs in power systems attributed to the attacks

Asif Iqbal, Andrii Shalaginov, Farhan Mahmood, 2018, 2018 IEEE International Conference on Big Data (Big Data).

IoT Digital Forensics Readiness in the Edge: A Roadmap for Acquiring Digital Evidences from Intelligent Smart Applications

Asif Iqbal, Andrii Shalaginov, Johannes Olegård, 2020, EDGE.

Soft Computing and Hybrid Intelligence for Decision Support in Forensics Science

Andrii Shalaginov, 2016, 2016 IEEE Conference on Intelligence and Security Informatics (ISI).

Fuzzy Logic Model for Digital Forensics: A Trade-off between Accuracy, Complexity and Interpretability

Andrii Shalaginov, Andrii Shalaginov, 2017, IJCAI.

Cybersecurity Awareness and Culture in Rural Norway

Vasileios Gkioulos, Mazaher Kianpour, Andrii Shalaginov, 2019, HAISA.

Automated generation of fuzzy rules from large-scale network traffic analysis in digital forensics investigations

Katrin Franke, Andrii Shalaginov, K. Franke, 2015, 2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR).

Multinomial classification of web attacks using improved fuzzy rules learning by Neuro-Fuzzy

Katrin Franke, Andrii Shalaginov, K. Franke, 2016, Int. J. Hybrid Intell. Syst..

Study of Soft Computing Methods for Large-Scale Multinomial Malware Types and Families Detection

Katrin Franke, Andrii Shalaginov, Lars Strande Grini, 2016, WCSC.

MEML: Resource-aware MQTT-based Machine Learning for Network Attacks Detection on IoT Edge Devices

Oleksandr Semeniuta, Mamoun Alazab, Andrii Shalaginov, 2019, UCC Companion.

A New Method for an Optimal SOM Size Determination in Neuro-Fuzzy for the Digital Forensics Applications

Katrin Franke, Andrii Shalaginov, 2015, IWANN.

PACER: Platform for Android Malware Classification, Performance Evaluation and Threat Reporting

Andrii Shalaginov, Shishir K. Shandilya, Ajit Kumar, 2020, Future Internet.

Evolutionary optimization of on-line multilayer perceptron for similarity-based access control

Andrii Shalaginov, Andrii Shalaginov, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Generation of the human-understandable fuzzy rules from large-scale datasets for Digital Forensics applications using Neuro-Fuzzy

Katrin Franke, Andrii Shalaginov, 2015 .

Smart Policing for a Smart World Opportunities, Challenges and Way Forward

Andrii Shalaginov, Muhammad Mudassar Yamin, Basel Katt, 2020, Advances in Intelligent Systems and Computing.

Automatic rule-extraction for malware detection on mobile devices

Andrii Shalaginov, Andrii Shalaginov, 2013 .

Intelligent generation of fuzzy rules for network firewalls based on the analysis of large-scale network traffic dumps

Katrin Franke, Andrii Shalaginov, K. Franke, 2017, Int. J. Hybrid Intell. Syst..

Identification of Attack-based Digital Forensic Evidences for WAMPAC Systems

Asif Iqbal, Mathias Ekstedt, Andrii Shalaginov, 2018, 2018 IEEE International Conference on Big Data (Big Data).

Cyber crime investigations in the era of big data

Katrin Franke, Andrii Shalaginov, Jan William Johnsen, 2017, 2017 IEEE International Conference on Big Data (Big Data).

Memory access patterns for malware detection

Katrin Franke, Sergii Banin, Andrii Shalaginov, 2016 .

Data-driven Approach to Information Sharing using Data Fusion and Machine Learning for Intrusion Detection

Katrin Franke, Andrii Shalaginov, Lars Christian Andersen, 2016 .

Comparing Open Source Search Engine Functionality, Efficiency and Effectiveness with Respect to Digital Forensic Search

Katrin Franke, Andrii Shalaginov, Joachim Hansen, 2018 .

Automated intelligent multinomial classification of malware species using dynamic behavioural analysis

Katrin Franke, Andrii Shalaginov, 2016, 2016 14th Annual Conference on Privacy, Security and Trust (PST).

RESPOnSE—A Framework for Enforcing Risk-Aware Security Policies in Constrained Dynamic Environments

Andrea Saracino, Vasileios Gkioulos, Athanasios Rizos, 2020, Sensors.

Towards Improvement of Multinomial Classification Accuracy of Neuro-Fuzzy for Digital Forensics Applications

Katrin Franke, Andrii Shalaginov, K. Franke, 2016, HIS.

Deep Graph neural network-based spammer detection under the perspective of heterogeneous cyberspace

Keping Yu, Mamoun Alazab, Andrii Shalaginov, 2021, Future Gener. Comput. Syst..

Big data analytics by automated generation of fuzzy rules for Network Forensics Readiness

Katrin Franke, Andrii Shalaginov, K. Franke, 2017, Appl. Soft Comput..

BCFL logging: An approach to acquire and preserve admissible digital forensics evidence in cloud ecosystem

Nazaraf Shah, Andrii Shalaginov, Mamoun Alazab, 2021, Future Gener. Comput. Syst..

Securing Smart Future: Cyber Threats and Intelligent Means to Respond

Tor-Morten Grønli, Andrii Shalaginov, 2021, 2021 IEEE International Conference on Big Data (Big Data).

Securing Resource-Constrained IoT Nodes: Towards Intelligent Microcontroller-Based Attack Detection in Distributed Smart Applications

Muhammad Ajmal Azad, Andrii Shalaginov, M. A. Azad, 2021, Future Internet.