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- W3196198025 abstract "Different attacks are done on data confidentiality, integrity, and availability. A famous type of network attacks is Port Scanning. Port Scanning attacks are done by attackers to know gather information about the devices and to know what services are running on. This study focuses on detecting port scanning attacks by using different machine learning algorithms and comparing between them to find the best one. Some algorithms reach near 100 percent of accuracy with detecting this type of attacks like Decision Tree and Random Forest with short time of training and testing." @default.
- W3196198025 created "2021-08-30" @default.
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- W3196198025 date "2021-08-10" @default.
- W3196198025 modified "2023-09-23" @default.
- W3196198025 title "Port-Scanning Attack Detection Using Supervised Machine Learning Classifiers" @default.
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- W3196198025 doi "https://doi.org/10.1109/esmarta52612.2021.9515743" @default.
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