Frame Synchronization Word Identification of Link Layer Protocol Based on Artificial Immune

LI Xinhao; ZHANG Min

doi:10.11999/JEIT160476

Volume 39 Issue 3

Mar. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(3): 561-567

LI Xinhao, ZHANG Min. Frame Synchronization Word Identification of Link Layer Protocol Based on Artificial Immune[J]. Journal of Electronics & Information Technology, 2017, 39(3): 561-567. doi: 10.11999/JEIT160476

Citation:

LI Xinhao, ZHANG Min. Frame Synchronization Word Identification of Link Layer Protocol Based on Artificial Immune[J]. Journal of Electronics & Information Technology, 2017, 39(3): 561-567. doi: 10.11999/JEIT160476

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Frame Synchronization Word Identification of Link Layer Protocol Based on Artificial Immune

doi: 10.11999/JEIT160476 cstr: 32379.14.JEIT160476

LI Xinhao¹,
ZHANG Min¹

Funds:

The National Natural Science Foundation of China (61171170), The Natural Science Foundation of Anhui Province (1408085QF115)

Received Date: 2016-05-10
Rev Recd Date: 2016-09-09
Publish Date: 2017-03-19

Abstract

Abstract

Inspired by biologic immune system, a novel frame synchronization word identification algorithm based on artificial immune is proposed. Firstly, due to the calculation of ODN concentration of known protocol type file set, ODN library of synchronization word in corresponding protocol is constructed. Then, through uniform continuity matching between ODN library of synchronization word and relevant file set, the detecting synchronization word gene library is constructed. At last, through calculating similarity value and uniform continuity matching by using ODN library of synchronization word and detecting gene library, synchronization word can be identified exactly. The new method, which has higher accurate recognition than pattern matching algorithm suggested by simulation results, has significant potential in engineering application.
- Frame structure,
- Synchronization word,
- Artificial immune,
- Negative selection,
- Similarity value

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References(29)

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