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Combining Popularity and Locality to Enhance In-Network Caching Performance and Mitigate Pollution Attacks in Content-Centric Networking
Author(s) -
Guozhi Zhang,
Jiqiang Liu,
Xiaolin Chnag,
Zhi Chen
Publication year - 2017
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2017.2754058
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Content-centric networking (CCN) aims to improve network reliability, scalability, and security by changing the way that information is organized and retrieved in the current Internet. One critical issue in CCN is in-network cache allocation. It is known that in-network caching mechanisms are vulnerable to distributed denial of service attacks, especially to pollution attacks. That is, a caching mechanism under pollution attacks cannot work well. The past years witnessed kinds of proposals of cache allocation mechanisms. However, none of them could effectively allocate in-network cache while defending against attacks. In this paper, we propose a lightweight non-collaborative cache allocation approach (IFDD), which could not only enhance in-network caching performance in terms of the cache hit ratio and the request processing delay, but also defend against pollution attacks. By lightweight, we mean that IFDD generates low communication overhead (due to non-collaboration) and computational overhead at routers. The key idea behind IFDD is to combine the content popularity with the content locality in making caching decision. Extensive simulation results on ndnSIM platform demonstrate the capability of the proposed approach in improving cache allocation performance while reducing the impact of pollution attacks.

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