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2018 | OriginalPaper | Chapter

CLEF: Limiting the Damage Caused by Large Flows in the Internet Core

Authors : Hao Wu, Hsu-Chun Hsiao, Daniele E. Asoni, Simon Scherrer, Adrian Perrig, Yih-Chun Hu

Published in: Cryptology and Network Security

Publisher: Springer International Publishing

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Abstract

The detection of network flows that send excessive amounts of traffic is of increasing importance to enforce QoS and to counter DDoS attacks. Large-flow detection has been previously explored, but the proposed approaches can be used on high-capacity core routers only at the cost of significantly reduced accuracy, due to their otherwise too high memory and processing overhead. We propose CLEF, a new large-flow detection scheme with low memory requirements, which maintains high accuracy under the strict conditions of high-capacity core routers. We compare our scheme with previous proposals through extensive theoretical analysis, and with an evaluation based on worst-case-scenario attack traffic. We show that CLEF outperforms previously proposed systems in settings with limited memory.

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Footnotes
1
As in prior literature [12, 34], the term large flow denotes a flow that sends more than its allocated bandwidth.
 
2
The IP metadata consists of source and destination addresses, protocol number, and ports. Thus, it requires about 16 bytes and 40 bytes per counter for IPv4 and IPv6, respectively.
 
3
The terms “counter tree” and “virtual counter” are also used by Chen et al. [7], but our technique differs in both approach and goal. Chen et al. efficiently manage a sufficient number of counters for per-flow accounting, while RLFD manages an insufficient number of counters to detect consistent overuse.
 
4
If \(T_{\ell } \ll \beta /\gamma \), it is hard for a large flow to reach the burst threshold \(\beta \) in such a short time; if \(T_{\ell } \gg \beta /\gamma \), the detection delay is too long, resulting in excessive damage.
 
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Metadata
Title
CLEF: Limiting the Damage Caused by Large Flows in the Internet Core
Authors
Hao Wu
Hsu-Chun Hsiao
Daniele E. Asoni
Simon Scherrer
Adrian Perrig
Yih-Chun Hu
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-030-00434-7_5

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