IPv6Landmarker: Enhancing IPv6 Street-Level Geolocation Through Network Landmark Mining and Targeted Updates

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-01-08 DOI:10.1109/TNSE.2025.3527563

Ruosi Cheng;Shichang Ding;Liancheng Zhang;Ruixiang Li;Shaoyong Du;Xiangyang Luo

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引用次数: 0

Abstract

IP geolocation accuracy heavily relies on the availability of numerous high-quality network landmarks. However, IPv6 geolocation faces challenges due to its vast address space and rotating prefixes. Existing landmark mining methods struggle to meet the stringent demands of IPv6 street-level geolocation. We introduce IPv6Landmarker, a novel approach that enhances IPv6 geolocation precision through landmark mining and targeted updates. By associating WAN IPv6 addresses with WiFi BSSIDs in wireless routers, we employ a multi-association coordinate filtering algorithm to select reliable IPv6 street-level landmarks. We also implement targeted updates based on IPv6 prefix rotation patterns. Using real-world data, we demonstrate significant improvements, including a range increase of 16.75% to 46.68% in candidate landmarks acquired globally and of 10.06% to 126.39% in landmarks acquired specifically within target cities. In particular, there is a range of 16.67% to 66.67% enhancement in the geolocation success of ground truth landmarks, coupled with a range of 6.09% to 40.34% reduction in geolocation error. Additionally, it shows a remarkable 82.36% improvement in landmark set stability.

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IPv6Landmarker：通过网络地标挖掘和定向更新增强 IPv6 街道级地理定位功能

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.