Kayes, A. S. M.

Cybersecurity data science: an overview from machine learning perspective

Sarker, I. H., Kayes, A. S. M., Badsha, S., Alqahtani, H., Watters, P., & Ng, A. (2020) · Journal of Big Data

Network Security and Intrusion DetectionInformation and Cyber Security

Cited by 766

Effectiveness analysis of machine learning classification models for predicting personalized context-aware smartphone usage

Sarker, I. H., Kayes, A. S. M., & Watters, P. (2019) · Journal of Big Data

Context-Aware Activity Recognition SystemsData Mining and Machine Learning Applications

Cited by 287

Ransomware Mitigation in the Modern Era: A Comprehensive Review, Research Challenges, and Future Directions

McIntosh, T., Kayes, A. S. M., Chen, Y.-P. P., Ng, A., & Watters, P. (2022) · ACM Computing Surveys

Advanced Malware Detection TechniquesSecurity and Verification in Computing

Cited by 146

ABC-RuleMiner: User behavioral rule-based machine learning method for context-aware intelligent services

Sarker, I. H., & Kayes, A. S. M. (2020) · Journal of Network and Computer Applications

Data Mining Algorithms and ApplicationsContext-Aware Activity Recognition Systems

Cited by 75

Controlling astroturfing on the internet: a survey on detection techniques and research challenges

Mahbub, S., Pardede, E., Kayes, A. S. M., & Rahayu, W. (2019) · International Journal of Web and Grid Services

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 29

IoT streaming data integration from multiple sources

Tu, D. Q., Kayes, A. S. M., Rahayu, W., & Nguyen, K. (2020) · Computing

Advanced Database Systems and QueriesData Quality and Management

Cited by 28