TY - JOUR
T1 - Distributed denial of service attack detection in application layer based on user behavior
AU - Bravo, Silvia
AU - Mauricio, David
PY - 2018/12/1
Y1 - 2018/12/1
N2 - © 2018, Silvia Bravo and David Mauricio. Distributed Denial of Service (DDoS) attacks are a threat to the security of red. In recent years, these attacks have been directed especially towards the application layer. This phenomenon is mainly due to the large number of existing tools for the generation of this type of attack. The highest detection rate achieved by a method in the application capacity is 98.5 percent. Therefore, the problem of detecting DDoS attacks persists. In this work an alternative of detection based on the dynamism of the web user is proposed. To do this, evaluate the user's characteristics, mouse functions and right click. For the evaluation, a data set of 11055 requests was used, from which the characteristics were extracted and entered into a classification algorithm. To that end, it can be applied once in Java for the classification of real users and DDoS attacks. The results showed that the evaluated characteristics achieved an efficiency of 100 percent. Therefore, it is concluded that these characteristics show the dynamism of the user and can be used in a detection method of DDoS attacks.
AB - © 2018, Silvia Bravo and David Mauricio. Distributed Denial of Service (DDoS) attacks are a threat to the security of red. In recent years, these attacks have been directed especially towards the application layer. This phenomenon is mainly due to the large number of existing tools for the generation of this type of attack. The highest detection rate achieved by a method in the application capacity is 98.5 percent. Therefore, the problem of detecting DDoS attacks persists. In this work an alternative of detection based on the dynamism of the web user is proposed. To do this, evaluate the user's characteristics, mouse functions and right click. For the evaluation, a data set of 11055 requests was used, from which the characteristics were extracted and entered into a classification algorithm. To that end, it can be applied once in Java for the classification of real users and DDoS attacks. The results showed that the evaluated characteristics achieved an efficiency of 100 percent. Therefore, it is concluded that these characteristics show the dynamism of the user and can be used in a detection method of DDoS attacks.
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M3 - Article
SN - 1735-188X
SP - 38
EP - 53
JO - Webology
JF - Webology
ER -