Um Sistema Inteligente para Detecção de DDoS em Ambientes Inteligentes baseado em Fog and Cloud Computing
Abstract
Urban spaces are engrafting Smart Environments (SE) to develop infrastructure, resources and services nowadays. SEs are composed of a huge number of heterogeneous devices (personal and IoT devices). One of the existing problems of SEs is the detection of distributed denial of service (DDoS) attacks, due to the vulnerabilities of IoT devices. It is necessary, therefore, to implement solutions that can detect DDoS in SEs, dealing with issues such as scalability, adaptability and heterogeneity. In this context, this paper presents an Intelligent System for detection of DDoS in SEs, applying machine learning approach (ML), fog computing and cloud computing. Besides that, the research presents a study on the most important traffic characteristics for the detection of DDoS in SEs, as well as a traffic segmentation approach to improve the accuracy of the system. The experiments performed, using real network traffic, suggest that the proposed system reaches 99% accuracy while reducing the volume of data exchanged and the detection time.
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