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A broad learning-based comprehensive defence against SSDP reflection attacks in IoTs

Digital Communications and Networks 2023年第5期9卷 1180-1189页

作者： Xin Liu Liang Zheng sumi helal Weishan Zhang Chunfu Jia Jiehan Zhou College of Computer Science and Technology China University of Petroleum(East China)QingdaoChina School of Computing Lancaster University UK Nankai University TianjinChina Information Technology and Electrical Engineering University of OuluFinland

The proliferation of Internet of Things(IoT)rapidly increases the possiblities of Simple Service Discovery Protocol(SSDP)reflection *** DDoS attack defence strategies deploy only to a certain type of devices in the attack chain,and need to detect attacks in advance,and the detection of DDoS attacks often uses heavy algorithms consuming lots of computing *** paper proposes a comprehensive DDoS attack defence approach which combines broad learning and a set of defence strategies against SSDP attacks,called Broad Learning based Comprehensive Defence(BLCD).The defence strategies work along the attack chain,starting from attack sources to *** defends against attacks without detecting attacks or identifying the roles of IoT devices in SSDP reflection *** also detects suspicious traffic at bots,service providers and victims by using broad learning,and the detection results are used as the basis for automatically deploying defence strategies which can significantly reduce DDoS *** evaluations,we thoroughly analyze attack traffic when deploying BLCD to different defence *** show that BLCD can reduce the number of packets received at the victim to 39 without affecting the standard SSDP service,and detect malicious packets with an accuracy of 99.99%.

关键词： Denial-of-service DRDoS SSDP reflection Attack Broad learning Traffic detection

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