摘要
从链路层未加密数据与已加密数据的随机统计特性角度出发,提出了一种基于随机性检测的链路层加密数据识别方法,解决了未知网络中的链路层加密数据及未加密数据样本获得问题.在基于随机性检测的链路层加密数据识别基础上,结合小波分解的多尺度特性,提出了基于小波分解的链路层加密数据识别方法,解决了方案实施过程中小波选择、特征参数提取、模板匹配及阈值选择等关键问题.研究结果表明:提出的方法具有更好的适用性及更高的识别率.对某无线网络链路层加密与未加密数据的识别率均达到95%以上.
From the random statistical properties of the encrypted data and plaintext in data link layer , an encrypted data identification method was proposed based on randomness test to solve the problem of obtaining the samples of encrypted data and plaintext in unknown network .Based on the random test and combined with the multi‐scale characteristic of wavelet decomposition ,another identification method was provided based on wavelet decomposition .The key issues such as wavelet selection ,char‐acteristic parameter extraction ,template matching and threshold selection were all solved in the meth‐od .The research results demonstrate that the proposed method is more applicable and has higher iden‐tification rate .T he identification rates of the proposed method are above 95% both to the encrypted data and plaintext in a wireless network .
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2015年第8期52-57,共6页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(61173191)
军内科研基金资助项目(YJJXM12033)
关键词
链路层
加密数据
随机性检测
小波分解
识别方法
data link layer
encrypted data
randomness test
wavelet decomposition
identification mehtod
