Evaluator: A Multilevel Decision Approach for Web-Based Landmark Evaluation. (15th July 2020)

• Record Type: Journal Article
• Authors: Yin, Meijuan; Yang, Wen; Liu, Xiaonan; Luo, Xiangyang
• Other Names: Galdi Clemente Academic Editor.
• Is Part Of: Security and communication networks. Volume 2020(2020)
• Publication Date: 2020-07-15
• Subjects: Computer networks -- Security measures -- Periodicals; Computer security -- Periodicals; Cryptography -- Periodicals; 005.805
• DOI: 10.1155/2020/8843188
• Languages: English
• ISSNs: 1939-0114

Abstract

Abstract : Street-level landmarks are an important basis for street-level IP geolocation, and the web-based landmark is one of the main sources of street-level landmarks. Considering the existing street-level landmark evaluation methods having low accuracy and strict constraints, this paper analyses the causes and evaluation idea of invalid web-based candidate landmarks and proposes Evaluator, a web-based landmark evaluation approach. Evaluator adopts the idea of the decision tree to filter invalid landmarks layer by layer and comprehensively estimates the quantitative reliability of candidate landmarks with public data and services to obtain reliable landmarks. This paper proposes the domain name system (DNS) distributed query algorithm to effectively resolve all IP addresses of a domain name, which provides data support for Evaluator to filter candidate landmarks. Meanwhile, this paper also proposes a reverse verification algorithm to obtain all domain names of an IP address, which provides an important reference to calculate the reliability of a reliable landmark. In addition, gradient descent is used to assess the parameters of the reliability estimating model, which effectively improves the robustness of Evaluator. Experiments show that reliable landmarks from Evaluator reduce the geolocation error of 100 targets in Hong Kong from 7.30 km to 3.91 km, compared with the landmark verifying method (LVM), one of the latest web-based landmark evaluation methods. Moreover, Evaluator significantly improves the evaluation coverage based on the same geolocation accuracy with street-level landmark evaluation (SLE), one of the latest landmark evaluation methods.