IP Geolocation Accuracy Evaluation Based on Crowdsourcing
Guangyu Zhu, Guoming Ren, Xiang Li, Xiaoye Li, Yongpeng Ti
Abstract
Open-access reader
Guangyu Zhu, Guoming Ren, Xiang Li, Xiaoye Li, Yongpeng Ti
Abstract
Open-access reader
Abstract IP geolocation is a crucial technology in the study of many fields, such as network measurement, fraud detection, and location-based advertising, etc. For over a decade, numerous researches and applications in this area have gained significant advances. In recent years, since more and more physical devices are connected to cyberspace, evaluating the accuracy of IP geolocation has gained much more attentions. In this paper, we first illustrate the concept and applications of the IP geolocation. Then, we design and propose an evaluation method on IP geolocation accuracy based on crowdsourcing. We evaluate the accuracy of a popular high-precision IP geolocation system and find out it reaches 98.88% correct on city-level geolocation, and the median error distance of street-level geolocation is 0.13km. Finally, the future development direction of IP geolocation accuracy evaluation is discussed.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Abstract IP geolocation is a crucial technology in the study of many fields, such as network measurement, fraud detection, and location-based advertising, etc. For over a decade, numerous researches and applications in this area have gained significant advances. In recent years, since more and more physical devices are connected to cyberspace, evaluating the accuracy of IP geolocation has gained much more attentions. In this paper, we first illustrate the concept and applications of the IP geolocation. Then, we design and propose an evaluation method on IP geolocation accuracy based on crowdsourcing. We evaluate the accuracy of a popular high-precision IP geolocation system and find out it reaches 98.88% correct on city-level geolocation, and the median error distance of street-level geolocation is 0.13km. Finally, the future development direction of IP geolocation accuracy evaluation is discussed.
Key concepts: Geolocation, Crowdsourcing, Computer science, The Internet, Data science, Data mining, World Wide Web