New Features of User’s Behavior to Distributed Denial of Service Attacks Detection in Application Layer

Abstract

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.

Enterprise Cyberspace Threat Landscape: An Analysis

“…The 2019 Coronavirus pandemic transformed the cyber security ecosystem by creating a "New Normal" in the cyberwar [4]. Enterprise systems, educational institutions, and organizations of all sizes moved their workforce to work from home without the adequate security apparatus in place [5][6][7][8]. This enterprise cyber-threat landscape is a collection of threats within the ecosystem, with information on identified vulnerability assets, risks, adversaries, and observed trends [9][10][11].…”