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author:

Chen, Xiang (Chen, Xiang.) [1] | Liu, Hongyan (Liu, Hongyan.) [2] | Huang, Qun (Huang, Qun.) [3] | Zhang, Dong (Zhang, Dong.) [4] (Scholars:张栋) | Zhou, Haifeng (Zhou, Haifeng.) [5] | Wu, Chunming (Wu, Chunming.) [6] | Liu, Xuan (Liu, Xuan.) [7]

Indexed by:

EI Scopus SCIE

Abstract:

To date, security researchers evaluate their solutions of mitigating distributed denial-of-service (DDoS) attacks via kernel-based or kernel-bypassing testing tools. However, kernelbased tools exhibit poor scalability in attack traffic generation while kernel-bypassing tools incur unacceptable monetary cost. We propose Excalibur, a scalable and low-cost testing framework for evaluating DDoS defense solutions. The key idea is to leverage the emerging programmable switch to empower testing tasks with Tbps-level scalability and low cost. Specifically, Excalibur offers intent-based primitives to enable academic researchers to customize testing tasks on demand. Moreover, in view of switch resource limitations, Excalibur coordinates both a server and a programmable switch to jointly perform testing tasks. It realizes flexible attack traffic generation, which requires a large number of resources, in the server while using the switch to increase the sending rate of attack traffic to Tbps-level. We have implemented Excalibur on a 64 x 100 Gbps Tofino switch. Our experiments on a 64 x 100 Gbps Tofino switch show that Excalibur achieves orders-of-magnitude higher scalability and lower cost than existing tools.

Keyword:

DDoS evaluation programmable switches

Community:

  • [ 1 ] [Chen, Xiang]Zhejiang Univ, Coll Comp Sci & Technol, Hangzhou 310027, Peoples R China
  • [ 2 ] [Liu, Hongyan]Zhejiang Univ, Coll Comp Sci & Technol, Hangzhou 310027, Peoples R China
  • [ 3 ] [Wu, Chunming]Zhejiang Univ, Coll Comp Sci & Technol, Hangzhou 310027, Peoples R China
  • [ 4 ] [Huang, Qun]Peking Univ, Dept Comp Sci & Technol, Beijing 100871, Peoples R China
  • [ 5 ] [Zhang, Dong]Fuzhou Univ, Coll Comp Sci & Big Data, Fuzhou 350025, Peoples R China
  • [ 6 ] [Zhou, Haifeng]Zhejiang Univ, Coll Control Sci & Engn, Hangzhou 310027, Peoples R China
  • [ 7 ] [Liu, Xuan]Yangzhou Univ, Coll Informat Engn, Coll Artificial Intelligence, Yangzhou 225012, Peoples R China
  • [ 8 ] [Liu, Xuan]Southeast Univ, Sch Comp Sci & Engn, Nanjing 211189, Peoples R China

Reprint 's Address:

  • [Zhou, Haifeng]Zhejiang Univ, Coll Control Sci & Engn, Hangzhou 310027, Peoples R China;;

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Source :

IEEE-ACM TRANSACTIONS ON NETWORKING

ISSN: 1063-6692

Year: 2023

Issue: 1

Volume: 32

Page: 191-206

3 . 0

JCR@2023

3 . 0 0 0

JCR@2023

ESI Discipline: COMPUTER SCIENCE;

ESI HC Threshold:32

JCR Journal Grade:2

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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