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Abstract
Users and organizations find it continuously challenging to deal with distributed denial of service (DDoS) attacks. . The security engineer works to keep a service available at all times by dealing with intruder attacks. The intrusion-detection system (IDS) is one of the solutions to detecting and classifying any anomalous behavior. The IDS system should always be updated with the latest intruder attack deterrents to preserve the confidentiality, integrity and availability of the service. In this paper, a new dataset is collected because there were no common data sets that contain modern DDoS attacks in different network layers, such as (SIDDoS, HTTP Flood). This work incorporates three well-known classification techniques: Multilayer Perceptron (MLP), Naive Bayes and Random Forest. The experimental results show that MLP achieved the highest accuracy rate (98.63%).
Highlights
Network security has become of utmost importance in all areas of business and industry, including bank transactions, Email, social media and university eServices, etc
Hackers are continually generating new types of Distributed Denial of Service (DDoS) which work on the application layer as well as the network layer
In order to understand the algorithm of the learning process on Multilayer Perceptron (MLP), suppose that a given MLP has N neurons in the input layer and M neurons in the hidden layers, and one output neuron
Summary
Network security has become of utmost importance in all areas of business and industry, including bank transactions, Email, social media and university eServices, etc. Many types of DDoS attacks are already known, such as a Smurf attack, which sends large numbers of Internet controlled message protocol packets to the intended victims Another type of DDoS is R-U-Dead-Yet (RUDY), which consumes all available sessions of a web application which means sessions will never end. One of the most up-to-date DDoS types is HTTP POST/GET, where attackers send a completely legitimate posted messages at a very slow rate, such as (1 byte/240 second), into a web server that is hosting a web application. We collected a completely new dataset in a controlled environment, which includes four harmful types of attack namely: UDP flood, Smurf, HTTP Flood and SIDDOS.
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