Research of Self-Set for Cloud Security Immune System Based on Bloom Filter

DOI

10.2991/csic-15.2015.112How to use a DOI?

Keywords

Cloud security, Human immune, Bloom filter

Abstract

In order to improve the performance of Cloud Security Immune System(CSIS), the representation and storage of the feature data of self-set is studied. Firstly, it proposes a Bloom Filter Self-Set storage model (BFSS), which can reduce the storage space of self-set effectively and save query time. Secondly, in order to support the delete operation of the feature data, it put forwards a Counting Bloom Filter Self-set storage model (CTBFSS). Finally, to reduce the storage space of self-set and reduce querying time further, it raises Compressed Bloom Filter Self-Set storage model (CPBFSS).Experiments demonstrate that BFSS, CTBFSS and CPBFSS can reduce the time cost between customer and service effectively on the premise of higher recognition rate, speed up the search procedure and improve the overall performance of the system.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lin Huo
AU  - Jingxiong Zhou
AU  - Yuchuan Xiao
PY  - 2015/07
DA  - 2015/07
TI  - Research of Self-Set for Cloud Security Immune System Based on Bloom Filter
BT  - Proceedings of the 2015 International Conference on Computer Science and Intelligent Communication
PB  - Atlantis Press
SP  - 460
EP  - 463
SN  - 2352-538X
UR  - https://doi.org/10.2991/csic-15.2015.112
DO  - 10.2991/csic-15.2015.112
ID  - Huo2015/07
ER  -