摘要
由于网络规模通常较大,拓扑结构复杂且动态性较高,如果受非法分子恶意入侵干扰,会提高隐私访问的风险。为此,提出新的基于拓扑结构优化的网络强隐私性访问安全监测方法。根据用户访问页面的浏览时间差判定用户的行为是否异常。优化拓扑结构,利用用户访问监控结果构建入侵访问结构,根据节点信誉值和阈值间的比较结果得出入侵监测结果,实现网络强隐私性访问安全监测。实验结果表明,在网络固定攻击和随机攻击两种情况下,所提方法的F1值一直较高。
Typically,large-scale networks have complex and dynamic topological structures.If they are maliciously invaded by illegal elements,the risk of privacy access will increase.Therefore,this paper proposes a monitoring method for strong privacy access security based on topological structure optimization.Firstly,we determined whether the user's behavior was abnormal according to the browsing time difference of the page accessed by the user.Then,we optimized the topological structure.Moreover,we used the user access monitoring results to construct the invasion access structure.By comparing the node credibility value and threshold,we got the intrusion monitoring result.Finally,we realized the security monitoring for strong privacy access in networks.Experimental results show that the F1 value of the proposed method is always high in the cases of fixed attack and random attack.
作者
苟钰
罗尚平
唐琴
COU Yu;LUO Shang-ping;TANG Qin(School of Electronic Information and Artificial Intelligence,Leshan Normal University,Leshan Sichuan 614000,China;Electronic Information Engineering Institute,Guilin University of Electronic Technology,Beihai Campus,Guilin Guangxi 536000,China)
出处
《计算机仿真》
2025年第4期332-335,362,共5页
Computer Simulation
关键词
拓扑结构
网络强隐私性访问
安全监测
信誉值
Topological structure
Strong privacy access
Security monitoring
Reputation value
