泛洪攻击下链路网络敏感数据防篡改仿真

Anti-Tampering Simulation of Sensitive Data of Link Network under Flood Attack

为提高敏感数据在链路网络中的安全性,需要研究网络敏感数据防篡改方法.采用当前方法对网络敏感数据做防篡改处理时,提取敏感数据所用的时间较长,处理后的敏感数据在链路网络中的安全性较低,存在敏感数据提取效率低和安全性低的问题.提出泛洪攻击下链路网络敏感数据防篡改方法,结合时间序列整体距离和局部变化特性,在相似测度计算过程中引入局部变化信息,通过滑动窗口分段方法提取网络敏感信息的特征,根据特征提取链路网络中存在的敏感信息.将混沌神经元的初始条件和联合矩阵作为密钥,生成混沌序列,采用混沌序列对敏感数据做加密处理,在泛洪攻击下防止链路敏感数据被篡改.仿真结果表明,所提方法的敏感数据提取效率高、安全性高.

In order to improve the security of sensitive data in the link network,it is necessary to research the tamper-proof method of network sensitive data. But the current methods are time - consuming in extracting sensitive data,resulting in low efficiency and low security. Therefore,a tamper - proof method of sensitive data in link network under flooding attacks was proposed. Combined with the overall distance and local variation characteristic of time series,we introduced local change information into the similarity measurement and then extracted characteristic of network sensitive information by sliding window segmentation method. Based on the features,we extracted sensitive information from the link network. After th at,we took initial condition of chaotic neuron and the joint matrix as the key to form the chaotic sequence. Finally,we used the chaotic sequence to encrypt the sensitive data,so as to prevent the link sensitive data from being tampered under the flooding attack. Simulation results show that the proposed method has higher efficiency and higher security in extracting sensitive data.