开放网络中分布式隐私数据主动防御仿真分析  

Simulation Analysis of Distributed Privacy Data In Open Network

作　　者：窦萌萌 程小辉[2] DOU Meng-meng;CHENG Xiao-hui(Hebi Institute of Engineering and Technology,Henan Polytechnic University,Hebi Henan 458030,China;College of Information Science and Engineering,Guilin University of Technology,Guilin Guangxi 541004,China)

机构地区：[1]河南理工大学鹤壁工程技术学院,河南鹤壁458030 [2]桂林理工大学信息科学与工程学院,广西桂林541004

出　　处：《计算机仿真》2023年第9期385-389,共5页Computer Simulation

基　　金：2017年度国家自然科学基金资助项目(61662017)。

摘　　要：由于开放网络自身存在较大的安全隐患,包含在其中的分布式隐私数据更易受黑客和其它非法手段的入侵和攻击,基于此提出一种开放网络中分布式隐私数据主动防御方法。分析分布式隐私数据的访问行为图谱基线,将其与URL子序列对比,判断访问数据用户的身份是否存在异常;针对异常身份用户展开DDOS攻击检测,一旦发现流量值异常及时启用主动防御模型,明确主动入侵列表,采用相应的防御等级完成对分布式隐私数据的主动防御。实验结果表明,所提方法可有效抵御DDOS攻击,取得了非常理想的主动防御效果,在降低攻击流量的同时能够保证正常用户流量不受影响。At present,the open network itself has significant risks,and the distributed private data is more vulnerable to intrusion and attack by hackers and other illegal means.As a result,an active defense method for distributed private data in open networks was proposed.Firstly,we analyzed the baseline of access behavior graph of distributed privacy data,and then compared it with the URL subsequence,thus determining whether there was an abnormality in the identity of the user accessing the data.Secondly,we performed the DDOS attack detection on the users with abnormal identities.Once abnormal traffic values were found,the active defense model must be activated in time.Meanwhile,the active intrusion list was specified.Finally,we completed the active defense of distributed private data according to the defense level.Experimental results show that the proposed method can effectively resist DDOS attacks and achieve an ideal active defense.In addition,this method can reduce the attack traffic while ensuring that the normal user traffic is not affected.

关 键 词：开放网络 分布式隐私数据 主动防御 攻击检测 防御数据 

分 类 号：TP375[自动化与计算机技术—计算机系统结构]