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Detecting The Intensity Of Denial-Of-Service Cyber Attacks Using Supervised Machine Learning, Abigail Hubbard
Detecting The Intensity Of Denial-Of-Service Cyber Attacks Using Supervised Machine Learning, Abigail Hubbard
Undergraduate Honors Theses
Denial-of-Service (DoS) attacks are aimed at shutting a machine or network down to block users from accessing it. These attacks can be difficult to detect and can cost millions in damages or lost earnings. Since the first DoS attack occurred in 1999, the way DoS attacks have been launched has become more complicated, making them more elusive and harder to detect. The first step to detect and mitigate a DoS attack is for a system to identify the malicious traffic.
In this experiment, we aim to identify the malicious traffic within ten seconds. To do this the project was divided …