Light-Weight DDoS Mitigation at Network Edge with Limited Resources
Title | Light-Weight DDoS Mitigation at Network Edge with Limited Resources |
Publication Type | Conference Paper |
Year of Publication | 2021 |
Authors | Yaegashi, Ryo, Hisano, Daisuke, Nakayama, Yu |
Conference Name | 2021 IEEE 18th Annual Consumer Communications Networking Conference (CCNC) |
Date Published | Jan. 2021 |
Publisher | IEEE |
ISBN Number | 978-1-7281-9794-4 |
Keywords | Communication system security, composability, Computer crime, computer network management, DDoS attack mitigation, denial-of-service attack, Floods, Human Behavior, Image edge detection, Internet of Things, Logic gates, Metrics, performance evaluation, pubcrawl, Queueing analysis, resilience, Resiliency, Resource management |
Abstract | The Internet of Things (IoT) has been growing rapidly in recent years. With the appearance of 5G, it is expected to become even more indispensable to people's lives. In accordance with the increase of Distributed Denial-of-Service (DDoS) attacks from IoT devices, DDoS defense has become a hot research topic. DDoS detection mechanisms executed on routers and SDN environments have been intensely studied. However, these methods have the disadvantage of requiring the cost and performance of the devices. In addition, there is no existing DDoS mitigation algorithm on the network edge that can be performed with the low-cost and low-performance equipment. Therefore, this paper proposes a light-weight DDoS mitigation scheme at the network edge using limited resources of inexpensive devices such as home gateways. The goal of the proposed scheme is to detect and mitigate flooding attacks. It utilizes unused queue resources to detect malicious flows by random shuffling of queue allocation and discard the packets of the detected flows. The performance of the proposed scheme was confirmed via theoretical analysis and computer simulation. The simulation results match the theoretical results and the proposed algorithm can efficiently detect malicious flows using limited resources. |
URL | https://ieeexplore.ieee.org/document/9369635 |
DOI | 10.1109/CCNC49032.2021.9369635 |
Citation Key | yaegashi_light-weight_2021 |
- Internet of Things
- resource management
- Resiliency
- resilience
- Queueing analysis
- pubcrawl
- performance evaluation
- Metrics
- Logic gates
- Communication system security
- Image edge detection
- Human behavior
- Floods
- denial-of-service attack
- DDoS attack mitigation
- computer network management
- Computer crime
- composability