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• W3131357908 startingPage "1294" @default.
• W3131357908 abstract "Network tomography is a powerful tool to monitor the internal state of a closed network that cannot be measured directly, with broad applications in the Internet, overlay networks, and all-optical networks. However, existing network tomography solutions all assume that the measurements are trust-worthy, leaving open how effective they are in an adversarial environment with possibly manipulated measurements. To understand the fundamental limit of network tomography in such a setting, we formulate and analyze a novel type of attack that aims at maximally degrading the performance of targeted paths without being localized by network tomography. By analyzing properties of the optimal attack strategy, we formulate novel combinatorial optimizations to design the optimal attack strategy, which are then linked to well-known NP-hard problems and approximation algorithms. As a byproduct, our algorithms also identify approximations of the most vulnerable set of links that once manipulated, can inflict the maximum performance degradation. Our evaluations on real topologies demonstrate the large potential damage of such attacks, signaling the need of new defenses." @default.
• W3131357908 created "2021-03-01" @default.
• W3131357908 creator A5027981537 @default.
• W3131357908 creator A5088400668 @default.
• W3131357908 date "2021-06-01" @default.
• W3131357908 modified "2023-09-27" @default.
• W3131357908 title "Stealthy DGoS Attack: DeGrading of Service Under the Watch of Network Tomography" @default.
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• W3131357908 doi "https://doi.org/10.1109/tnet.2021.3058230" @default.
• W3131357908 hasPublicationYear "2021" @default.
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