科技通报
科技通報
과기통보
BULLETIN OF SCIENCE AND TECHNOLOGY
2015年
6期
220-222
,共3页
局部特征%压缩采样%网络安全%检测
跼部特徵%壓縮採樣%網絡安全%檢測
국부특정%압축채양%망락안전%검측
local characteristic%compressive sampling%network security%detection
对网络入侵信号的准确检测,提高检测概率是保证网络安全的基础,传统检测方法难以实现对较低信噪比下的攻击信号的高效定位和检测,无法有效预测入侵信号的局部特征点,导致重采样,虚警概率和漏检概率较高。提出一种基于局部特征压缩采样的网络入侵信号检测算法,构建低信噪比下网络入侵信号模型,采用多普勒频移模糊搜索对入侵信号进行平滑处理,得到入侵信号的局部特征预测量和测量值,为了使得入侵检测适合线性实时处理过程,提高在低信噪比下的检测性能,采用卡尔曼滤波对结果进行修正,采用局部特征压缩采样判断入侵信号的联合特征,实现了对网络入侵信号的局部特征压缩采样检测。仿真结果表明,该算法检测性能较好,检测概率优于传统算法,展示了较好的应用价值,确保了网络安全。
對網絡入侵信號的準確檢測,提高檢測概率是保證網絡安全的基礎,傳統檢測方法難以實現對較低信譟比下的攻擊信號的高效定位和檢測,無法有效預測入侵信號的跼部特徵點,導緻重採樣,虛警概率和漏檢概率較高。提齣一種基于跼部特徵壓縮採樣的網絡入侵信號檢測算法,構建低信譟比下網絡入侵信號模型,採用多普勒頻移模糊搜索對入侵信號進行平滑處理,得到入侵信號的跼部特徵預測量和測量值,為瞭使得入侵檢測適閤線性實時處理過程,提高在低信譟比下的檢測性能,採用卡爾曼濾波對結果進行脩正,採用跼部特徵壓縮採樣判斷入侵信號的聯閤特徵,實現瞭對網絡入侵信號的跼部特徵壓縮採樣檢測。倣真結果錶明,該算法檢測性能較好,檢測概率優于傳統算法,展示瞭較好的應用價值,確保瞭網絡安全。
대망락입침신호적준학검측,제고검측개솔시보증망락안전적기출,전통검측방법난이실현대교저신조비하적공격신호적고효정위화검측,무법유효예측입침신호적국부특정점,도치중채양,허경개솔화루검개솔교고。제출일충기우국부특정압축채양적망락입침신호검측산법,구건저신조비하망락입침신호모형,채용다보륵빈이모호수색대입침신호진행평활처리,득도입침신호적국부특정예측량화측량치,위료사득입침검측괄합선성실시처리과정,제고재저신조비하적검측성능,채용잡이만려파대결과진행수정,채용국부특정압축채양판단입침신호적연합특정,실현료대망락입침신호적국부특정압축채양검측。방진결과표명,해산법검측성능교호,검측개솔우우전통산법,전시료교호적응용개치,학보료망락안전。
The accurate detection of network intrusion signal, improve the detection probability is the foundation of the net?work security, the traditional detection method is difficult to realize the efficient location of attack than the detection signal and low signal-to-noise, unable to effectively predict the local features of intrusion signal, resulting in re sampling, the proba?bility of false alarm and false detection probability is higher. Put forward a kind of local feature compression and network in?trusion detection algorithm based on signal sampling, construct an intrusion signal model under low signal to noise ratio of net?work, using the Doppler frequency shift fuzzy search intrusion signal smoothing, obtain the local characteristics of the intru?sion signal quantity prediction and the measured value, in order to make intrusion detection for linear real-time processing process, improve the low SNR detection performance, using Kalman filter to revise the results, using local feature compres?sion sampling determination combined features of intrusion signal, the realization of the local characteristics of the network in?trusion signal compression sampling detection. Simulation results show that this algorithm better detection performance than the traditional algorithm, the probability of detection, showing a good application value, to ensure network security.