TY - JOUR
T1 - New features of user's behavior to distributed denial of service attacks detection in application layer
AU - Bravo, Silvia
AU - Mauricio, David
PY - 2018/1/1
Y1 - 2018/1/1
N2 - © 2018 Kassel University Press GmbH. 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%. 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%. 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 Kassel University Press GmbH. 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%. 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%. 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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U2 - 10.3991/ijoe.v14i12.9439
DO - 10.3991/ijoe.v14i12.9439
M3 - Article
SN - 1868-1646
SP - 164
EP - 178
JO - International Journal of Online Engineering
JF - International Journal of Online Engineering
ER -