Loading [a11y]/accessibility-menu.js
High-performance, platform-independent DDoS detection for IoT ecosystems | IEEE Conference Publication | IEEE Xplore

High-performance, platform-independent DDoS detection for IoT ecosystems


Abstract:

Most Distributed Denial of Service (DDoS) detection and mitigation strategies for Internet of Things (IoT) are based on a remote cloud server or purpose-built middlebox e...Show More

Abstract:

Most Distributed Denial of Service (DDoS) detection and mitigation strategies for Internet of Things (IoT) are based on a remote cloud server or purpose-built middlebox executing complex intrusion detection methods, that impose stringent scalability and performance requirements on the IoT due to the vast amounts of traffic and devices to be handled. In this paper, we present an edge-based detection scheme using BPFabric, a high-speed, programmable data-plane switch architecture, and lightweight network functions to execute upstream anomaly detection. The proposed detection scheme ensures fast detection of DDoS attacks originated from IoT devices, while guaranteeing minimum resource usage and processing overhead. Our solution was compared against two widespread coarse-grained detection techniques, showing detection delays under 5ms, an overall accuracy of 93 - 95% and a bandwidth overhead of less than 1%.
Date of Conference: 14-17 October 2019
Date Added to IEEE Xplore: 13 February 2020
ISBN Information:
Print on Demand(PoD) ISSN: 0742-1303
Conference Location: Osnabrueck, Germany

References

References is not available for this document.