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Massachusetts Institute of Technology

Fundamental limit of network flow attacks

Abstract

dc:description.abstract

A network flow-based attack refers to a cyber-attack where the adversary seeks to block user traffic from transmission by sending adversarial traffic that reduces the available user capacity. In this thesis, we explore the fundamental limits of network flow attacks by investigating its feasibility region defined by the minimum resource required for a successful attack and designing optimal attacking strategies that achieve the feasibility region. First, we consider the case where the target network uses fixed-path routing and the adversary injects traffic into the network, encroaching the capacity of the network links and thus reducing the capacity available to network users on the fixed paths. We propose a new network interdiction paradigm that captures this phenomenon by modeling the network as a capacitated graph with the user throughput given by the max-flow value on the fixed user paths.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Fu, Xinzhe.
Advisor dc:contributor.advisor
  • Eytan Modiano.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/122412
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/122412

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Fu, Xinzhe.. Fundamental limit of network flow attacks. Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122412