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Investigating Impact of Fake-Type Content Poisoning Attack on NDN

Published: 29 August 2023 Publication History

Abstract

Information-centric networking (ICN) has been widely studied as a new network architecture for efficient content delivery. However, the threat of content poisoning attack (CPA) has been pointed out. In the CPA, a malicious user degrades the cache hit ratio of router caches by inserting fake contents into router caches. To investigate effective countermeasures against the CPA, we need to clarify the impact of the CPA on reducing the cache hit ratio. However, existing studies assumed limited CPA schemes, and they were based on small network topologies without considering caching methods and locations of fake contents and bots. In this paper, we focus on the original-fake type CPA which is the easiest CPA for attackers and most difficult to be detected, and we investigate the potential threat of the original-fake CPA for various caching methods on large-scale networks when optimally assigning locations of fake contents and bots.

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ARES '23: Proceedings of the 18th International Conference on Availability, Reliability and Security
August 2023
1440 pages
ISBN:9798400707728
DOI:10.1145/3600160
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 August 2023

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Author Tags

  1. ICN
  2. NDN
  3. content poisoning attack
  4. network topology

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ARES 2023

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Overall Acceptance Rate 228 of 451 submissions, 51%

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