Moutaz Alazab
Orcid: 0000-0003-2823-4776
According to our database1,
Moutaz Alazab
authored at least 24 papers
between 2011 and 2024.
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Bibliography
2024
Enhanced Android Ransomware Detection Through Hybrid Simultaneous Swarm-Based Optimization.
Cogn. Comput., September, 2024
A Novel IDS with a Dynamic Access Control Algorithm to Detect and Defend Intrusion at IoT Nodes.
Sensors, April, 2024
Natural language inference model for customer advocacy detection in online customer engagement.
Mach. Learn., April, 2024
Industry 4.0 Innovation: A Systematic Literature Review on the Role of Blockchain Technology in Creating Smart and Sustainable Manufacturing Facilities.
Inf., February, 2024
Expert Syst. J. Knowl. Eng., January, 2024
An Effective Networks Intrusion Detection Approach Based on Hybrid Harris Hawks and Multi-Layer Perceptron.
CoRR, 2024
2023
Expert Syst. Appl., July, 2023
Improving Semantic Information Retrieval Using Multinomial Naive Bayes Classifier and Bayesian Networks.
Inf., May, 2023
2022
Evolution of Industry and Blockchain Era: Monitoring Price Hike and Corruption Using BIoT for Smart Government and Industry 4.0.
IEEE Trans. Ind. Informatics, 2022
Expert Syst. Appl., 2022
Proceedings of the 14th International Joint Conference on Computational Intelligence, 2022
2021
Blockchain technology in supply chain management: an empirical study of the factors affecting user adoption/acceptance.
Clust. Comput., 2021
2020
Future Gener. Comput. Syst., 2020
2019
Trade-off among lean, agile, resilient and green paradigms: an empirical study on pharmaceutical industry in Jordan using a TOPSIS-entropy method.
Int. J. Adv. Oper. Manag., 2019
2012
Int. J. Secur. Networks, 2012
Int. J. Electron. Gov. Res., 2012
Proceedings of the International Symposium on Communications and Information Technologies, 2012
Proceedings of the 32nd International Conference on Distributed Computing Systems Workshops (ICDCS 2012 Workshops), 2012
2011
Proceedings of the Global Security, Safety and Sustainability & e-Democracy, 2011
Zero-day Malware Detection based on Supervised Learning Algorithms of API call Signatures.
Proceedings of the Ninth Australasian Data Mining Conference, AusDM 2011, Ballarat, 2011