| Ransomware: a survey and trends S Aurangzeb, M Aleem, MA Iqbal, MA Islam J. Inf. Assur. Secur 6 (2), 48-58, 2017 | 98 | 2017 |
| ML-DDoS: A blockchain-based multilevel DDoS mitigation mechanism for IoT environments RF Hayat, S Aurangzeb, M Aleem, G Srivastava, JCW Lin IEEE Transactions on Engineering Management, 2022 | 47 | 2022 |
| BigRC-EML: big-data based ransomware classification using ensemble machine learning S Aurangzeb, H Anwar, MA Naeem, M Aleem Cluster Computing 25 (5), 3405-3422, 2022 | 38 | 2022 |
| On the classification of Microsoft-Windows ransomware using hardware profile S Aurangzeb, RNB Rais, M Aleem, MA Islam, MA Iqbal PeerJ Computer Science 7, e361, 2021 | 26 | 2021 |
| Evaluation and classification of obfuscated Android malware through deep learning using ensemble voting mechanism S Aurangzeb, M Aleem Scientific Reports 13 (1), 3093, 2023 | 13 | 2023 |
| Rthreatdroid: A ransomware detection approach to secure iot based healthcare systems MJ Iqbal, S Aurangzeb, M Aleem, G Srivastava, JCW Lin IEEE Transactions on Network Science and Engineering, 2022 | 13 | 2022 |
| Cybersecurity for autonomous vehicles against malware attacks in smart-cities S Aurangzeb, M Aleem, MT Khan, H Anwar, MS Siddique Cluster Computing, 1-16, 2023 | 3 | 2023 |
| On the performance and scalability of simulators for improving security and safety of smart cities A Mohsin, S Aurangzeb, M Aleem, MT Khan 2022 IEEE 27th International Conference on Emerging Technologies and Factory …, 2022 | 3 | 2022 |
| A machine learning based hybrid approach to classify and detect windows ransomware S Aurangzeb MS (CS) dissertation, Capital Univ. Sci. Technol., Islamabad, Pakistan, 2018 | 2 | 2018 |
| Demand-side load forecasting in smart grids using machine learning techniques MY Masood, S Aurangzeb, M Aleem, A Chilwan, M Awais PeerJ Computer Science 10, e1987, 2024 | | 2024 |
| AndroDex: Android Dex images of obfuscated malware S Aurangzeb, M Aleem, MT Khan, G Loukas, G Sakellari Scientific Data 11 (1), 212, 2024 | | 2024 |
