Abstract
TCP SYNC flood DDoS attack is one of the commonly used attack in the computer network system. One of the novel method to detect the DDoS attack is the Dendritic Cell Algorithm (DCA). DCA is a kind of artificial immune system in the evolutionary algorithm that can be used is an anomaly detection. Artificial immune systems (AIS) are adaptive systems, inspired by theoretical immunology and observed immune functions, principles and models, which are applied to problem solving. The AIS suggest a multilayered protection structure for protecting the computer networks against the unauthorized attacks. The DCA is also designed to solve the problems in network intrusion detection system. The DCA is a population based algorithm, in which each agent in the system is represented as 'artificial DC'. Each DC has the ability to combine multiple data streams and can add context to data suspected as anomalous. The DCA shares the properties with certain filtering techniques. It provides information representing how anomalous a group of antigen is, not simply if a data item is anomalous or not. This can be achieved through the generation of an anomaly coefficient value, termed the Mature Context Antigen Value (MCAV). The main objectives of DCA are to improve the correlation factor, to minimized the false positive and false negative alarm generation and, to increase the rate of detection of intrusion.
Published Version
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