Proactive Botnet Detection: Through Characterization of Distributed Denial of Service Attacks - Softcover
Inhaltsangabe
In this quantitative quasi-experimental study two distributed denial of service attacks were captured and the characteristics of the attacks were used to detect botnets by identifying egressing distributed denial of service attack packets at the source of the attack. A sample Dark DDoSer botnet was constructed and used to launch a distributed denial of service attack. The characteristics of the distributed denial of service attacks were used as the independent variables in a quasi-experiment where network traffic was monitored with Snort to detect DDoS packets. The dependent variable for the experiment was false positive alerts for the DDoS packets. The findings showed that the characteristics of a distributed denial of service attack can be used to pro-actively detect botnets through egress monitoring.
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Über die Autorin bzw. den Autor
Dr. Hyslip is currently an adjunct faculty member at Norwich University and Wake Technical Community College. Dr. Hyslip received his Doctor of Science degree in Information Assurance from Capitol College in 2014, and he previously obtained a Master of Science degree from East Carolina University and a Bachelor of Science degree from Clarkson University. He is a Certified Ethical Hacker C|EH, and certified forensic examiner.
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Proactive Botnet Detection: Through Characterization of Distributed Denial of Service Attacks
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Createspace Independent Publishing Platform, 2015
ISBN 10: 1508433119
ISBN 13: 9781508433118
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Proactive Botnet Detection (Paperback)
Verlag:
Createspace Independent Publishing Platform, 2015
ISBN 10: 1508433119
ISBN 13: 9781508433118
Neu
Paperback
Anbieter: CitiRetail, Stevenage, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
Paperback. Zustand: new. Paperback. In this quantitative quasi-experimental study two distributed denial of service attacks were captured and the characteristics of the attacks were used to detect botnets by identifying egressing distributed denial of service attack packets at the source of the attack. A sample Dark DDoSer botnet was constructed and used to launch a distributed denial of service attack. The characteristics of the distributed denial of service attacks were used as the independent variables in a quasi-experiment where network traffic was monitored with Snort to detect DDoS packets. The dependent variable for the experiment was false positive alerts for the DDoS packets. The findings showed that the characteristics of a distributed denial of service attack can be used to pro-actively detect botnets through egress monitoring. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9781508433118
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