期刊名称：Journal of King Saud University @?C Computer and Information Sciences
印刷版ISSN：1319-1578
出版年度：2019
页码：1-7
DOI：10.1016/j.jksuci.2019.04.010
出版社：Elsevier
摘要：Fog computing (FC) is a contemporary computing paradigm that gives additional support to cloud environment by carrying out some local data analysis in edge of the devices, facilitating networking, computing, infrastructure and storage support as backbone for end user computing. Still enterprises are not convinced to use this as security and privacy are most of the open and challenging issues. Availability among the security requirements is the one which is about rendering on demand service to different client applications without any disruptions. It can often be demolished by Denial of service (DoS) and distributed denial of service (DDoS) attacks in fog and cloud computing environment. In this paper we propose a novel Source based DDoS defence mechanism which can be used in fog environment as well as the cloud environment to mitigate DDoS attacks. It makes use of Software Defined Network (SDN) to deploy the DDoS defender module at SDN controller to detect the anomalous behavior of DDoS attacks in Network/Transport level. The proposed work provides deep learning (DL) based detection method which makes use of the network traffic analysis mechanisms to filter and forward the legitimate packets to the server and can block the infected packets to cause further attacks.
关键词：Fog computing ; Deep learning ; DDoS attack ; Software defined network ; Openflow network
