| Deep learning approach for intelligent intrusion detection system R Vinayakumar, M Alazab, KP Soman, P Poornachandran, A Al-Nemrat, ... IEEE Access 7, 41525-41550, 2019 | 240 | 2019 |
| Organizations and cybercrime R Broadhurst, P Grabosky, M Alazab, B Bouhours Available at SSRN 2345525, 2013 | 198* | 2013 |
| Zero-day malware detection based on supervised learning algorithms of API call signatures M Alazab, S Venkatraman, P Watters, M Alazab Sydney, New South Wales: Australian Computer Society, 2010 | 186 | 2010 |
| Towards understanding malware behaviour by the extraction of API calls M Alazab, S Venkataraman, P Watters 2010 second cybercrime and trustworthy computing workshop, 52-59, 2010 | 148 | 2010 |
| Profiling and classifying the behavior of malicious codes M Alazab Journal of Systems and Software 100, 91-102, 2015 | 116 | 2015 |
| Robust intelligent malware detection using deep learning R Vinayakumar, M Alazab, KP Soman, P Poornachandran, ... IEEE Access 7, 46717-46738, 2019 | 92 | 2019 |
| Hybrids of support vector machine wrapper and filter based framework for malware detection S Huda, J Abawajy, M Alazab, M Abdollalihian, R Islam, J Yearwood Future Generation Computer Systems 55, 376-390, 2016 | 85 | 2016 |
| Hybrids of support vector machine wrapper and filter based framework for malware detection S Huda, J Abawajy, M Alazab, M Abdollalihian, R Islam, J Yearwood Future Generation Computer Systems 55, 376-390, 2016 | 81 | 2016 |
| Spam and crime R Broadhurst, M Alazab Regulatory Theory, 517, 2017 | 76* | 2017 |
| Malware Detection Based on Structural and Behavioural Features of API Calls M Alazab, R Layton, S Venkataraman, P Watters Proceedings of the 1st International Cyber Resilience Conference, 1-10, 2010 | 76 | 2010 |
| Cybercrime: the case of obfuscated malware M Alazab, S Venkatraman, P Watters, M Alazab, A Alazab Global security, safety and sustainability & e-Democracy, 204-211, 2011 | 66 | 2011 |
| Using feature selection for intrusion detection system A Alazab, M Hobbs, J Abawajy, M Alazab 2012 international symposium on communications and information technologies …, 2012 | 64 | 2012 |
| Artificial intelligence for detection, estimation, and compensation of malicious attacks in nonlinear cyber-physical systems and industrial IoT F Farivar, MS Haghighi, A Jolfaei, M Alazab IEEE transactions on industrial informatics 16 (4), 2716-2725, 2019 | 63 | 2019 |
| Analysis of malicious and benign android applications M Alazab, V Moonsamy, L Batten, P Lantz, R Tian 2012 32nd International Conference on Distributed Computing Systems …, 2012 | 62 | 2012 |
| A novel PCA-firefly based XGBoost classification model for intrusion detection in networks using GPU S Bhattacharya, PKR Maddikunta, R Kaluri, S Singh, TR Gadekallu, ... Electronics 9 (2), 219, 2020 | 61 | 2020 |
| An analysis of the nature of groups engaged in cyber crime R Broadhurst, P Grabosky, M Alazab, B Bouhours, S Chon An analysis of the nature of groups engaged in cyber crime, International …, 2014 | 58 | 2014 |
| Early detection of diabetic retinopathy using PCA-firefly based deep learning model TR Gadekallu, N Khare, S Bhattacharya, S Singh, PK Reddy Maddikunta, ... Electronics 9 (2), 274, 2020 | 53 | 2020 |
| Machine learning based botnet identification traffic A Azab, M Alazab, M Aiash 2016 IEEE Trustcom/BigDataSE/ISPA, 1788-1794, 2016 | 53* | 2016 |
| Performance evaluation of e‐government services using balanced scorecard S Alhyari, M Alazab, S Venkatraman, M Alazab, A Alazab Benchmarking: an international journal, 2013 | 52 | 2013 |
| Effective digital forensic analysis of the NTFS disk image M Alazab, S Venkatraman, P Watters Ubiquitous Computing and Communication Journal 4 (1), 551-558, 2009 | 52* | 2009 |
