| Are we ready for SDN? Implementation challenges for software-defined networks S Sezer, S Scott-Hayward, PK Chouhan, B Fraser, D Lake, J Finnegan, ... IEEE Communications magazine 51 (7), 36-43, 2013 | 1438 | 2013 |
| A survey of security in software defined networks S Scott-Hayward, S Natarajan, S Sezer IEEE Communications Surveys & Tutorials 18 (1), 623-654, 2015 | 642 | 2015 |
| SDN security: A survey S Scott-Hayward, G O'Callaghan, S Sezer 2013 IEEE SDN For Future Networks and Services (SDN4FNS), 1-7, 2013 | 635 | 2013 |
| Deep android malware detection N McLaughlin, J Martinez del Rincon, BJ Kang, S Yerima, P Miller, ... Proceedings of the seventh ACM on conference on data and application …, 2017 | 582 | 2017 |
| A multimodal deep learning method for android malware detection using various features TG Kim, BJ Kang, M Rho, S Sezer, EG Im IEEE Transactions on Information Forensics and Security 14 (3), 773-788, 2018 | 556 | 2018 |
| DL-Droid: Deep learning based android malware detection using real devices MK Alzaylaee, SY Yerima, S Sezer Computers & Security 89, 101663, 2020 | 412 | 2020 |
| A new android malware detection approach using bayesian classification SY Yerima, S Sezer, G McWilliams, I Muttik 2013 IEEE 27th international conference on advanced information networking …, 2013 | 374 | 2013 |
| Obfuscation: The hidden malware P O'Kane, S Sezer, K McLaughlin IEEE Security & Privacy 9 (5), 41-47, 2011 | 300 | 2011 |
| STRIDE-based threat modeling for cyber-physical systems R Khan, K McLaughlin, D Laverty, S Sezer 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT …, 2017 | 298 | 2017 |
| STPA-SafeSec: Safety and security analysis for cyber-physical systems I Friedberg, K McLaughlin, P Smith, D Laverty, S Sezer Journal of information security and applications 34, 183-196, 2017 | 297 | 2017 |
| High accuracy android malware detection using ensemble learning SY Yerima, S Sezer, I Muttik IET Information Security 9 (6), 313-320, 2015 | 228 | 2015 |
| Droidfusion: A novel multilevel classifier fusion approach for android malware detection SY Yerima, S Sezer IEEE transactions on cybernetics 49 (2), 453-466, 2018 | 222 | 2018 |
| Analysis of Bayesian classification‐based approaches for Android malware detection SY Yerima, S Sezer, G McWilliams IET Information Security 8 (1), 25-36, 2014 | 209 | 2014 |
| Multiattribute SCADA-specific intrusion detection system for power networks Y Yang, K McLaughlin, S Sezer, T Littler, EG Im, B Pranggono, HF Wang IEEE Transactions on Power Delivery 29 (3), 1092-1102, 2014 | 204 | 2014 |
| Threat analysis of blackenergy malware for synchrophasor based real-time control and monitoring in smart grid R Khan, P Maynard, K McLaughlin, D Laverty, S Sezer 4th International Symposium for ICS & SCADA Cyber Security Research 2016, 53-63, 2016 | 202 | 2016 |
| Android malware detection using parallel machine learning classifiers SY Yerima, S Sezer, I Muttik 2014 Eighth international conference on next generation mobile apps …, 2014 | 193 | 2014 |
| A multi-classifier network-based crypto ransomware detection system: A case study of locky ransomware AO Almashhadani, M Kaiiali, S Sezer, P O’Kane IEEE access 7, 47053-47067, 2019 | 186 | 2019 |
| Multidimensional intrusion detection system for IEC 61850-based SCADA networks Y Yang, HQ Xu, L Gao, YB Yuan, K McLaughlin, S Sezer IEEE Transactions on Power Delivery 32 (2), 1068-1078, 2016 | 185 | 2016 |
| Evolution of ransomware P O'Kane, S Sezer, D Carlin Iet Networks 7 (5), 321-327, 2018 | 157 | 2018 |
| Impact of cyber-security issues on smart grid Y Yang, T Littler, S Sezer, K McLaughlin, HF Wang 2011 2nd IEEE PES International Conference and Exhibition on Innovative …, 2011 | 135 | 2011 |
