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Street-Level ip geolocation Algorithm Based on Landmarks Clustering

Computers, Materials & Continua 2021年第3期66卷 3345-3361页

作者： Fan Zhang Fenlin Liu Rui Xu Xiangyang Luo Shichang Ding Hechan Tian PLA Strategic Support Force Information Engineering University Zhengzhou450001China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001China Cyberspace Security Key Laboratory of Sichuan Province Chengdu610000China China Electronic Technology Cyber Security Co. Ltd.Chengdu610000China University of Goettingen Goettingen37075Germany

Existing ip geolocation algorithms based on delay similarity often rely on the principle that geographically adjacent ips have similar ***,this principle is often invalid in real Internet environment,which leads to unreliable geolocation *** improve the accuracy and reliability of locating ip in real Internet,a street-level ip geolocation algorithm based on landmarks clustering is ***,we use the probes to measure the known landmarks to obtain their delay vectors,and cluster landmarks using ***,the landmarks are clustered again by their latitude and longitude,and the intersection of these two clustering results is taken to form training ***,we train multiple neural networks to get the mapping relationship between delay and location in each training ***,we determine one of the neural networks for the target by the delay similarity and relative hop counts,and then geolocate the target by this *** it brings together the delay and geographical coordinates clustering,the proposed algorithm largely improves the inconsistency between them and enhances the mapping relationship between *** evaluate the algorithm by a series of experiments in Hong Kong,Shanghai,Zhengzhou and New *** experimental results show that the proposed algorithm achieves street-level ip geolocation,and comparing with existing typical streetlevel geolocation algorithms,the proposed algorithm improves the geolocation reliability significantly.

关键词： ip geolocation neural network landmarks clustering delay similarity relative hop

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Towards ip geolocation with intermediate routers based on topology discovery

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Cybersecurity 2018年第1期1卷 500-513页

作者： Zhihao Wang Hong Li Qiang Li Wei Li Hongsong Zhu Limin Sun Institute of Information Engineering Chinese Academy of Sciences BeijingChina School of Cyber Security University of Chinese Academy of SciencesBeijingChina School of Computer and Information Technology Beijing Jiaotong UniversityBeijingChina Department of Computer Science Georgia State UniversityAtlantaGeorgia

ip geolocation determines geographical location by the ip address of Internet *** geolocation is widely used by target advertising,online fraud detection,cyber-attacks attribution and so *** has gained much more attentions in these years since more and more physical devices are connected to *** geolocation methods cannot resolve the geolocation accuracy for those devices with few landmarks *** this paper,we propose a novel geolocation approach that is based on common routers as secondary landmarks(Common Routers-based geolocation,CRG).We search plenty of common routers by topology discovery among web server *** use statistical learning to study localized(delay,hop)-distance correlation and locate these common *** locate the accurate positions of common routers and convert them as secondary landmarks to help improve the feasibility of our geolocation system in areas that landmarks are sparsely *** manage to improve the geolocation accuracy and decrease the maximum geolocation error compared to one of the state-of-the-art geolocation *** the end of this paper,we discuss the reason of the efficiency of our method and our future research.

关键词： ip geolocation Network topology discovery Web landmarks Relative latency Statistical learning

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Delay-Distance Correlation Study for ip geolocation

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Wuhan University Journal of Natural Sciences 2017年第2期22卷 157-164页

作者： DING Shichang LUO Xiangyang YE Dengpan LIU Fenlin The State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001 Henan China School of Computer Wuhan University Wuhan 430072Hubei China

Although many classical ip geolocation algorithms are suitable to rich-connected networks, their performances are seriously affected in poor-connected networks with weak delay-distance correlation. This paper tries to improve the performances of classical ip geolocation algorithms by finding rich-connected sub-networks inside poor-connected networks. First, a new delay-distance correlation model （RTD-Corr model） is proposed. It builds the relationship between delay-distance correlation and actual network factors such as the tortuosity of the network path and the ratio of propagation delay. Second, based on the RTD-Corr model and actual network characteristics, this paper discusses about how to find rich-connected networks inside China Intemet which is a typical actual poor-connected network. Then we find rich-connected sub-networks of China Intemet through a large-scale network measurement which covers three major ISPs and thirty provinces. At last, based on the founded rich-connected sub-networks, we modify two classical ip geolocation algorithms and the experiments in China Intemet show that their accuracy is significantly increased.

关键词： ip geolocation delay-distance correlation network security network measurement rich-connected sub-networks

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Street-Level Landmarks Acquisition Based on SVM Classifiers

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Computers, Materials & Continua 2019年第5期59卷 591-606页

作者： Ruixiang Li Yingying Liu Yaqiong Qiao Te Ma Bo Wang Xiangyang Luo State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001China Zhengzhou Science and Technology Institute Zhengzhou450001China Henan Institute of Animal Husbandry Economics Zhengzhou450044China State University of New York at Buffalo New York14260-1660United States

High-density street-level reliable landmarks are one of the important foundations for street-level ***,the existing methods cannot obtain enough street-level landmarks in a short period of *** this paper,a street-level landmarks acquisition method based on SVM(Support Vector Machine)classifiers is ***,the port detection results of ips with known services are vectorized,and the vectorization results are used as an input of the SVM ***,the kernel function and penalty factor are adjusted for SVM classifiers training,and the optimal SVM classifiers are *** that,the classifier sequence is constructed,and the ips with unknown service are classified using the ***,according to the domain name corresponding to the ip,the relationship between the classified server ip and organization name is *** experimental results in Guangzhou and Wuhan city in China show that the proposed method can be as a supplement to existing typical methods since the number of obtained street-level landmarks is increased substantially,and the median geolocation error using evaluated landmarks is reduced by about 2 km.

关键词： Landmarks acquisition SVM street-level ip geolocation

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基于用户来源信息的中国天气网全局负载调整方法

基于用户来源信息的中国天气网全局负载调整方法

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第31届中国气象学会年会

作者：李雁鹏中国气象局公共气象服务中心

作为中国气象局面向公众提供气象信息服务的核心门户,中国天气网部分业务因天气原因往往遇到暴增的突发访问高峰。为解决暴增访问量,详细分析了旧有全局负载系统中存在的不能准确识别用户来源、无法精细调整负载、带宽不足服务布局不灵... 详细信息

作为中国气象局面向公众提供气象信息服务的核心门户,中国天气网部分业务因天气原因往往遇到暴增的突发访问高峰。为解决暴增访问量,详细分析了旧有全局负载系统中存在的不能准确识别用户来源、无法精细调整负载、带宽不足服务布局不灵活、负载结果调整无法直观展示等问题。通过采用权威ip地址来源信息库、结合粗细粒度调控方法、调整网络服务布局并增加带宽总量、设计开发基于访问日志分析的用户来源访问实时监控系统,提出并实现了基于用户来源信息的中国天气网全局负载调整新方法。运用全局负载调整新方法及时调控突发负载,成功应对了多次业务流量突发高峰。

关键词：域名系统全局负载调整 ip geolocation iRules 日志分析日志监控

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