| Title |
A DDoS attacks traceback scheme for SDN-based smart city |
| ID_Doc |
36564 |
| Authors |
Chen, W; Xiao, SC; Liu, LJ; Jiang, XQ; Tang, ZB |
| Title |
A DDoS attacks traceback scheme for SDN-based smart city |
| Year |
2020 |
| Published |
|
| DOI |
10.1016/j.compeleceng.2019.106503 |
| Abstract |
Smart City (SC) has brought tremendous opportunities and exciting challenges. Network security is one of the most important challenges in SC networks. Software-Defined Networking (SDN) is more likely to be the target of Distributed Denial of Service (DDoS) attacks due to the risk of a single point of failure. To better defend against DDoS attacks, we focus on tracing the source and propose a statistics-based traceback scheme using the advantages of the SDN architecture. We analyze the changes of flow through the Base Station (BS) nodes to calculate the eigenvalue and establish the anomaly tree. Then prune it with DDoS detection algorithm to get the attack path. Through the experiments, we obtain the optimal parameters to make the proposed scheme more flexible and effective. It shows that the scheme consumes fewer network resources and saves time than traditional ones while keeping the DDoS defense accuracy at a high level. (C) 2019 Elsevier Ltd. All rights reserved. |
| Author Keywords |
Smart city; Anomaly detection; Software-defined networking; Distributed denial of service; Traceback |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000518675000019 |
| WoS Category |
Computer Science, Hardware & Architecture; Computer Science, Interdisciplinary Applications; Engineering, Electrical & Electronic |
| Research Area |
Computer Science; Engineering |
| PDF |
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