基于量子谐振子的RoQ攻击识别方法
|
摘要
针对当前降质服务攻击给TCP服务质量带来的问题,提出了一种基于量子谐振子算法的RoQ攻击识别方法.该方法以量子谐振子为载波,计算量子谐振子从高能态向基本态转变过程,以此监测统计异常网络流和数据包丢失变化,对降质攻击进行识别.实验结果表明,该方法能够有效刻画漏检率、丢失率等参数变化,准确识别降质攻击.
In order to improve the current degradation of service attacks to reduce TCP's service quality,a RoQ attack recognition method is presented by quantum oscillator algorithm.In this method,the quantum harmonic oscillator is set as the carrier,and is calculated the transition from high-energy state to the base state of quantum oscillator.So,the abnormal network traffic and the change of packet loss aremonitored and counted,and the degraded attack is identified.The experiment results show that,this method caneffect depict the factors,such as missed inspectionrate and loss rate,and accurately identify the degraded attack.
In order to improve the current degradation of service attacks to reduce TCP's service quality,a RoQ attack recognition method is presented by quantum oscillator algorithm.In this method,the quantum harmonic oscillator is set as the carrier,and is calculated the transition from high-energy state to the base state of quantum oscillator.So,the abnormal network traffic and the change of packet loss aremonitored and counted,and the degraded attack is identified.The experiment results show that,this method caneffect depict the factors,such as missed inspectionrate and loss rate,and accurately identify the degraded attack.
引文
[1]胡云山,申意,曾光,等.针对减宽SHA-1算法的模差分攻击分析[J].四川大学学报:自然科学版,2016,53:1041.
[2]Yang H,Luo H,Ye F.Security in mobile ad hoc network:Challenge and solution[J].IEEE Wirel Commun,2004,11:38.
[3]施江勇,鲜明,王会梅,等.基于随机Petri网模型的降质服攻防效果评估[J].计算机科学,2014,41:58.
[4]文坤,杨家海,张宾.低速率拒绝服务攻击研究与进展综述[J].软件学报,2014,25:591.
[5]文坤,杨家海,程凤娟,等.骨干网络中RoQ攻击的检测、定位和识别[J].计算机研究与发展,2015,52:813.
[6]Yang X,Ke L,Wan L.Low-rate DDoS attacks detection and traceback by using new information metrics[J].IEEE Trans Inf Foren Sec,2011,6:424.
[7]彭天炜.采用负熵目标函数和自相关成分的攻击流检测[J].科技通报,2014,30:83.
[8]邓兵,陶然,平殿发.基于分数阶傅里叶变换补偿多普勒徙动的动目标检测算法[J].兵工学报,2009,30:1034.
[9]Chang Y L,Lin T L.Network-based AVC whole frame loss visibility model and frame dropping methods[J].IEEE Trans Image Process,2012,21:3353.
[10]任炜,刘腾红,金海.移动Ad Hoc网络中针对拥塞的RoQDDoS攻击及其防御[J].计算机研究与发展,2006,43:1927.
[11]欧世峰,高颖,赵晓晖.自适应组合型盲源分离算法及其优化方案[J].电子与信息学报,2011,33:1243.
[12]荣宏,王会梅,鲜明,等.基于快速独立成分分析的RoQ攻击检测方法[J].电子与信息学报,2013,35:2307.
[13]付小红,杨小牛,刘乃安.基于四阶累积量的稳健的通信信号盲分离算法[J].电子与信息学报,2008,30:1853.
[14]Ralph A.Recognizing emotion from facial expressions:psychological and neurological mechanisms[J].Behav Congitive Neurosci Rev,2002,1:21.
[15]王鹏,黄焱,任超,等.多尺度量子谐振子高维函数全局优化算法[J].电子学报,2013,41:2465.
[16]黄焱,王鹏,程琨,等.多尺度量子谐振子优化算法的并行性研究[J].通信学报,2016,37:67.
[17]王鹏,黄焱,袁亚男,等.多尺度量子谐振子算法的收敛特性[J].电子学报,2016,44:1987.
[18]燕京京,王鹏,范家兵,等.基于量子谐振子模型的聚类中心选取算法[J].电子学报,2016,44:405.
[2]Yang H,Luo H,Ye F.Security in mobile ad hoc network:Challenge and solution[J].IEEE Wirel Commun,2004,11:38.
[3]施江勇,鲜明,王会梅,等.基于随机Petri网模型的降质服攻防效果评估[J].计算机科学,2014,41:58.
[4]文坤,杨家海,张宾.低速率拒绝服务攻击研究与进展综述[J].软件学报,2014,25:591.
[5]文坤,杨家海,程凤娟,等.骨干网络中RoQ攻击的检测、定位和识别[J].计算机研究与发展,2015,52:813.
[6]Yang X,Ke L,Wan L.Low-rate DDoS attacks detection and traceback by using new information metrics[J].IEEE Trans Inf Foren Sec,2011,6:424.
[7]彭天炜.采用负熵目标函数和自相关成分的攻击流检测[J].科技通报,2014,30:83.
[8]邓兵,陶然,平殿发.基于分数阶傅里叶变换补偿多普勒徙动的动目标检测算法[J].兵工学报,2009,30:1034.
[9]Chang Y L,Lin T L.Network-based AVC whole frame loss visibility model and frame dropping methods[J].IEEE Trans Image Process,2012,21:3353.
[10]任炜,刘腾红,金海.移动Ad Hoc网络中针对拥塞的RoQDDoS攻击及其防御[J].计算机研究与发展,2006,43:1927.
[11]欧世峰,高颖,赵晓晖.自适应组合型盲源分离算法及其优化方案[J].电子与信息学报,2011,33:1243.
[12]荣宏,王会梅,鲜明,等.基于快速独立成分分析的RoQ攻击检测方法[J].电子与信息学报,2013,35:2307.
[13]付小红,杨小牛,刘乃安.基于四阶累积量的稳健的通信信号盲分离算法[J].电子与信息学报,2008,30:1853.
[14]Ralph A.Recognizing emotion from facial expressions:psychological and neurological mechanisms[J].Behav Congitive Neurosci Rev,2002,1:21.
[15]王鹏,黄焱,任超,等.多尺度量子谐振子高维函数全局优化算法[J].电子学报,2013,41:2465.
[16]黄焱,王鹏,程琨,等.多尺度量子谐振子优化算法的并行性研究[J].通信学报,2016,37:67.
[17]王鹏,黄焱,袁亚男,等.多尺度量子谐振子算法的收敛特性[J].电子学报,2016,44:1987.
[18]燕京京,王鹏,范家兵,等.基于量子谐振子模型的聚类中心选取算法[J].电子学报,2016,44:405.