%0 Journal Article
%T 云计算中基于可用带宽欧氏距离的LDoS攻击检测方法<br>An approach of detecting LDoS attacks based on the euclidean distance of available bandwidth in cloud computing
%A 岳猛
%A 吴志军
%A 姜军
%J 山东大学学报（理学版）
%D 2016
%R 10.6040/j.issn.1671-9352.3.2015.090
%X 摘要： 根据云计算数据中心网络(data center networks, DCNS)架构的特点,从网络架构的角度对低速率拒绝服务(low-rate denial of service, LDoS)攻击进行建模。提出基于可用带宽欧氏距离的LDoS攻击检测方法,其本质是依据LDoS攻击导致同一路由域内所有链路可用带宽同时增大的特征,将可用带宽的平均欧氏距离作为LDoS攻击检测测度。改进了传统的探测间隔模型(probe gap model, PGM),并将其专门用于云计算环境下的可用带宽测量。在实际的网络环境中对LDoS攻击效果和LDoS检测性能进行测试,结果表明:1)DCNS内的LDoS攻击比洪水式拒绝服务(flooding denial of service, FDoS)攻击更具危害;2)所提出的检测方法能够准确检测LDoS攻击,检测率达到98%。<br>Abstract: According to the architecture of the cloud computing Data Center Networks(DCNs), the Low-rate Denial of Service(LDoS)attack is modeled from the view of network architecture. Furthermore, the euclidean approach is applied to the available bandwidth to detect LDoS attacks. As LDoS attacks force the links co-located in the same routing domain to increase their available bandwidths, the average euclidean distance is applied as the measurement for detecting LDoS attacks. And then, the traditional Probe Gap Model(PGM)is improved to test the available bandwidth specifically in cloud computing. Experiments in practical network are conducted to test the attack effect and the detection performance. Test results verify: 1)LDoS attacks present more damages than Flooding Denial of Service(FDoS)attacks in cloud computing DCNs, 2)The proposed detection approach can detect LDoS attack accurately, and achieves 98% detection probability
%K 云计算
%K 可用带宽
%K 欧氏距离
%K 低速率拒绝服务攻击
%K 攻击检测
%K &lt
%K br&gt
%K cloud computing
%K available bandwidth
%K attack detection
%K euclidean distance
%K low-rate denial of service attack
%U http://lxbwk.njournal.sdu.edu.cn/CN/10.6040/j.issn.1671-9352.3.2015.090