Quantitative Risk, Statistical Methods and the Four Quadrants for Information Security. - Gaute Wangen; Andrii Shalaginov (CRiSIS, 2015)

A new method of fuzzy patches construction in Neuro-Fuzzy for malware detection. - Andrii Shalaginov; Katrin Franke (IFSA-EUSFLAT, 2015)

Towards Improvement of Multinomial Classification Accuracy of Neuro-Fuzzy for Digital Forensics Applications. - Andrii Shalaginov; Katrin Franke (HIS, 2015)

A New Method for an Optimal SOM Size Determination in Neuro-Fuzzy for the Digital Forensics Applications. - Andrii Shalaginov; Katrin Franke (IWANN (2), 2015)

Automated generation of fuzzy rules from large-scale network traffic analysis in digital forensics investigations. - Andrii Shalaginov; Katrin Franke (SoCPaR, 2015)

Understanding Neuro-Fuzzy on a class of multinomial malware detection problems. - Andrii Shalaginov; Lars Strande Grini; Katrin Franke (IJCNN, 2016)

Soft Computing and Hybrid Intelligence for Decision Support in Forensics Science. - Andrii Shalaginov (ISI, 2016)

Cyber Security Risk Assessment of a DDoS Attack. - Gaute Wangen; Andrii Shalaginov; Christoffer Hallstensen (ISC, 2016)

Automated intelligent multinomial classification of malware species using dynamic behavioural analysis. - Andrii Shalaginov; Katrin Franke (PST, 2016)

Study of Soft Computing Methods for Large-Scale Multinomial Malware Types and Families Detection. - Lars Strande Grini; Andrii Shalaginov; Katrin Franke (WCSC, 2016)

Multinomial classification of web attacks using improved fuzzy rules learning by Neuro-Fuzzy. - Andrii Shalaginov; Katrin Franke (Int. J. Hybrid Intell. Syst., 2016)

Intelligent generation of fuzzy rules for network firewalls based on the analysis of large-scale network traffic dumps. - Andrii Shalaginov; Katrin Franke (Int. J. Hybrid Intell. Syst., 2016)

Cyber crime investigations in the era of big data. - Andrii Shalaginov; Jan William Johnsen; Katrin Franke (IEEE BigData, 2017)

Dynamic feature-based expansion of fuzzy sets in Neuro-Fuzzy for proactive malware detection. - Andrii Shalaginov (FUSION, 2017)

Fuzzy Logic Model for Digital Forensics: A Trade-off between Accuracy, Complexity and Interpretability. - Andrii Shalaginov (IJCAI, 2017)

Evolutionary optimization of on-line multilayer perceptron for similarity-based access control. - Andrii Shalaginov (IJCNN, 2017)

A deep neuro-fuzzy method for multi-label malware classification and fuzzy rules extraction. - Andrii Shalaginov; Katrin Franke (SSCI, 2017)

Big data analytics by automated generation of fuzzy rules for Network Forensics Readiness. - Andrii Shalaginov; Katrin Franke (Appl. Soft Comput., 2017)

Identification of Attack-based Digital Forensic Evidences for WAMPAC Systems. - Asif Iqbal 012; Farhan Mahmood; Andrii Shalaginov; Mathias Ekstedt (IEEE BigData, 2018)

Intelligent analysis of digital evidences in large-scale logs in power systems attributed to the attacks. - Asif Iqbal 012; Andrii Shalaginov; Farhan Mahmood (IEEE BigData, 2018)

Machine Learning Aided Static Malware Analysis: A Survey and Tutorial. - Andrii Shalaginov; Sergii Banin; Ali Dehghantanha; Katrin Franke (CoRR, 2018)

PACE: Platform for Android Malware Classification and Performance Evaluation. - Ajit Kumar 001; Vinti Agarwal; Shishir K. Shandilya; Andrii Shalaginov; Saket Upadhyay; Bhawna Yadav (IEEE BigData, 2019)

Cybercrime Investigations in the Era of Smart Applications: Way Forward Through Big Data. - Andrii Shalaginov; Igor Kotsiuba; Asif Iqbal 012 (IEEE BigData, 2019)

Cybersecurity Awareness and Culture in Rural Norway. - Håkon Gunleifsen; Vasileios Gkioulos; Gaute Wangen; Andrii Shalaginov; Mazaher Kianpour; Mohamed Abomhara (HAISA, 2019)

MEML: Resource-aware MQTT-based Machine Learning for Network Attacks Detection on IoT Edge Devices. - Andrii Shalaginov; Oleksandr Semeniuta; Mamoun Alazab (UCC Companion, 2019)

Smart Home Forensics: An Exploratory Study on Smart Plug Forensic Analysis. - Asif Iqbal 012; Johannes Olegård; Ranjana Ghimire; Shirin Jamshir; Andrii Shalaginov (IEEE BigData, 2020)

Modern Cybercrime Investigation: Technological Advancement of Smart Devices and Legal Aspects of Corresponding Digital Transformation. - Andrii Shalaginov; Marina Shalaginova; Aleksandar Jevremovic; Marko Krstic (IEEE BigData, 2020)

IoT Digital Forensics Readiness in the Edge: A Roadmap for Acquiring Digital Evidences from Intelligent Smart Applications. - Andrii Shalaginov; Asif Iqbal 012; Johannes Olegård (EDGE, 2020)

Intelligent mobile malware detection using permission requests and API calls. - Moutaz Alazab; Mamoun Alazab; Andrii Shalaginov; Abdelwadood Mesleh; Albara W. Awajan (Future Gener. Comput. Syst., 2020)

Predicting likelihood of legitimate data loss in email DLP. - Mohamed Falah Faiz; Junaid Arshad; Mamoun Alazab; Andrii Shalaginov (Future Gener. Comput. Syst., 2020)

Big Data Analytics and Artificial Intelligence for Cyber Crime Investigation and Prevention. - Andrii Shalaginov (Future Gener. Comput. Syst., 2020)

PACER: Platform for Android Malware Classification, Performance Evaluation and Threat Reporting. - Ajit Kumar 001; Vinti Agarwal; Shishir K. Shandilya; Andrii Shalaginov; Saket Upadhyay; Bhawna Yadav (Future Internet, 2020)

Decentralized Self-Enforcing Trust Management System for Social Internet of Things. - Muhammad Ajmal Azad; Samiran Bag; Feng Hao 001; Andrii Shalaginov (IEEE Internet Things J., 2020)

RESPOnSE - A Framework for Enforcing Risk-Aware Security Policies in Constrained Dynamic Environments. - Christina Michailidou; Vasileios Gkioulos; Andrii Shalaginov; Athanasios Rizos; Andrea Saracino (Sensors, 2020)

Securing Smart Future: Cyber Threats and Intelligent Means to Respond. - Andrii Shalaginov; Tor-Morten Grønli (IEEE BigData, 2021)

BCFL logging: An approach to acquire and preserve admissible digital forensics evidence in cloud ecosystem. - Kenny Awuson-David; Tawfik Al Hadhrami; Mamoun Alazab; Nazaraf Shah; Andrii Shalaginov (Future Gener. Comput. Syst., 2021)

Deep Graph neural network-based spammer detection under the perspective of heterogeneous cyberspace. - Zhiwei Guo; Lianggui Tang; Tan Guo; Keping Yu; Mamoun Alazab; Andrii Shalaginov (Future Gener. Comput. Syst., 2021)

Securing Resource-Constrained IoT Nodes: Towards Intelligent Microcontroller-Based Attack Detection in Distributed Smart Applications. - Andrii Shalaginov; Muhammad Ajmal Azad (Future Internet, 2021)

Artificial Intelligence Enabled Middleware for Distributed Cyberattacks Detection in IoT-based Smart Environments. - Guru Prasad Bhandari; Andreas Lyth; Andrii Shalaginov; Tor-Morten Grønli (IEEE Big Data, 2022)

A Novel Architectural Framework on IoT Ecosystem, Security Aspects and Mechanisms: A Comprehensive Survey. - Mohammed Bouzidi; Nishu Gupta; Faouzi Alaya Cheikh; Andrii Shalaginov; Mohammad Omar Derawi (IEEE Access, 2022)

Hybrid IoT Cyber Range. - Karl Edvard Balto; Muhammad Mudassar Yamin; Andrii Shalaginov; Basel Katt (Sensors, 2023)

An Overview of Smart Home IoT Trends and related Cybersecurity Challenges. - Ivan Cvitic; Dragan Perakovic; Marko Perisa; Aleksandar Jevremovic; Andrii Shalaginov (Mob. Networks Appl., 2023)

VulnMiner: A comprehensive framework for vulnerability collection from C/C++ source code projects. - Guru Prasad Bhandari; Nikola Gavric; Andrii Shalaginov (Softw. Impacts, 2024)

IoTvulCode: AI-enabled vulnerability detection in software products designed for IoT applications. - Guru Prasad Bhandari; Gebremariam Assres; Nikola Gavric; Andrii Shalaginov; Tor-Morten Grønli (Int. J. Inf. Sec., 2024)

Towards Resource-Efficient DDoS Detection in IoT: Leveraging Feature Engineering of System and Network Usage Metrics. - Nikola Gavric; Guru Prasad Bhandari; Andrii Shalaginov (J. Netw. Syst. Manag., 2024)

Patient-Centric Hierarchical Federated Learning for Heart Rate Prediction. - Bithi Banik; Debasish Ghose; Yuan Lin; Andrii Shalaginov (ICHI, 2025)

Generating vulnerability security fixes with Code Language Models. - Guru Prasad Bhandari; Nikola Gavric; Andrii Shalaginov (Inf. Softw. Technol., 2025)

Energy Efficiency of Kernel and User Space Level VPN Solutions in AIoT Networks. - Aleksandar Jevremovic; Zona Kostic; Ivan Chorbev; Dragan Perakovic; Andrii Shalaginov; Ivan Cvitic (IEEE Open J. Comput. Soc., 2025)

State-of-the-Art and Challenges of Engineering ML- Enabled Software Systems in the Deep Learning Era. - Gebremariam Assres; Guru Prasad Bhandari; Andrii Shalaginov; Tor-Morten Grønli; Gheorghita Ghinea (ACM Comput. Surv., 2025)