| Unsupervised anomaly based botnet detection in IoT networks S Nõmm, H Bahşi 2018 17th IEEE international conference on machine learning and applications …, 2018 | 119 | 2018 |
| Dimensionality reduction for machine learning based iot botnet detection H Bahşi, S Nõmm, FB La Torre 2018 15th International Conference on Control, Automation, Robotics and …, 2018 | 112 | 2018 |
| MedBIoT: Generation of an IoT botnet dataset in a medium-sized IoT network. A Guerra-Manzanares, J Medina-Galindo, H Bahsi, S Nõmm ICISSP, 207-218, 2020 | 105 | 2020 |
| Kronodroid: Time-based hybrid-featured dataset for effective android malware detection and characterization A Guerra-Manzanares, H Bahsi, S Nõmm Computers & Security 110, 102399, 2021 | 69 | 2021 |
| Hybrid feature selection models for machine learning based botnet detection in IoT networks A Guerra-Manzanares, H Bahsi, S Nomm 2019 International Conference on Cyberworlds (CW), 324-327, 2019 | 55 | 2019 |
| Threat modeling of cyber-physical systems-a case study of a microgrid system SM Khalil, H Bahsi, H Ochieng’Dola, T Korõtko, K McLaughlin, V Kotkas Computers & Security 124, 102950, 2023 | 26 | 2023 |
| Android malware concept drift using system calls: detection, characterization and challenges A Guerra-Manzanares, M Luckner, H Bahsi Expert Systems with Applications 206, 117200, 2022 | 22 | 2022 |
| In-depth feature selection for the statistical machine learning-based botnet detection in IoT networks R Kalakoti, S Nõmm, H Bahsi IEEE Access 10, 94518-94535, 2022 | 22 | 2022 |
| The cyber-insurance market in Norway H Bahşi, U Franke, EL Friberg Information & Computer Security 28 (1), 54-67, 2020 | 22 | 2020 |
| Impact assessment of cyber actions on missions or business processes: A systematic literature review H Bahşi, CJ Udokwu, U Tatar, A Norta ICCWS 2018 13th International Conference on Cyber Warfare and Security, 11, 2018 | 22 | 2018 |
| Concept drift and cross-device behavior: Challenges and implications for effective android malware detection A Guerra-Manzanares, M Luckner, H Bahsi Computers & Security 120, 102757, 2022 | 20 | 2022 |
| Classification of confidential documents by using adaptive neurofuzzy inference systems E Alparslan, A Karahoca, H Bahşi Procedia Computer Science 3, 1412-1417, 2011 | 19 | 2011 |
| Impact assessment of cyber attacks: A quantification study on power generation systems. U Tatar, H Bahsi, G Adrian 11th System of Systems Engineering Conference (SoSE), 1-6, 2016 | 16 | 2016 |
| Towards the integration of a post-hoc interpretation step into the machine learning workflow for IoT botnet detection A Guerra-Manzanares, S Nõmm, H Bahsi 2019 18th IEEE International Conference On Machine Learning And Applications …, 2019 | 14 | 2019 |
| Capability detection and evaluation metrics for cyber security lab exercises E Caliskan, U Tatar, H Bahsi, R Ottis, R Vaarandi ICMLG2017 5th International Conference on Management Leadership and …, 2017 | 12 | 2017 |
| Leveraging the first line of defense: A study on the evolution and usage of android security permissions for enhanced android malware detection A Guerra-Manzanares, H Bahsi, M Luckner Journal of Computer Virology and Hacking Techniques 19 (1), 65-96, 2023 | 11 | 2023 |
| A cyber attack taxonomy for microgrid systems H Bahsi, H Ochieng‘Dola, SM Khalil, T Korõtko 2022 17th Annual System of Systems Engineering Conference (SOSE), 324-331, 2022 | 11 | 2022 |
| A machine learning-based forensic tool for image classification-A design science approach JR Del Mar-Raave, H Bahşi, L Mršić, K Hausknecht Forensic Science International: Digital Investigation 38, 301265, 2021 | 11 | 2021 |
| In-depth Feature Selection and Ranking for Automated Detection of Mobile Malware. A Guerra-Manzanares, S Nomm, H Bahsi ICISSP 1, 274-283, 2019 | 11 | 2019 |
| Time-frame analysis of system calls behavior in machine learning-based mobile malware detection A Guerra-Manzanares, S Nõmm, H Bahsi 2019 International Conference on Cyber Security for Emerging Technologies …, 2019 | 10 | 2019 |
