USENIX ATC2022顶会
AddrMiner: A Comprehensive Global Active IPv6 Address Discovery System
Guanglei Song, Jiahai Yang, Lin He, Zhiliang Wang, Guo Li, Chenxin Duan, Yaozhong Liu, Zhongxiang Sun
摘要
Fast Internet-wide scanning is essential for network situational awareness and asset evaluation. However, the vast IPv6 address space makes brute-force scanning infeasible. Although state-of-the-art techniques have made effective attempts, these methods do not work in seedless regions, while the detection efficiency is low in regions with seeds. Moreover, the constructed hitlists with low coverage cannot truly represent the active IPv6 address landscape of the Internet.
This paper introduces AddrMiner, a systematic and comprehensive global active IPv6 address probing system. We divide the IPv6 address space regions into three kinds according to the number of seed addresses to discover active IPv6 addresses from scratch, from few to many. For the regions with no seeds, we present AddrMiner-N , leveraging an organization association strategy to mine active addresses. It fills the gap of address probing in seedless regions and finds active addresses covering 86.4K IPv6 prefixes announced by BGP, accounting for 81.6% of the probed announced prefixes. For the regions with few seeds, we propose AddrMiner-F , utilizing a similarity matching strategy to probe active addresses further. The hit rate of active address probing is improved by 70%-150% compared to existing algorithms. Moreover, for the regions with sufficient seeds, we present AddrMiner-S to generate target addresses based on reinforcement learning dynamically. It nearly doubles the hit rate compared to the state-of-the-art algorithms. Finally, we deploy AddrMiner and discover 2.1 billion active IPv6 addresses, including 1.7 billion de-aliased active addresses and 0.4 billion aliased addresses, through continuous probing for 13 months. We would like to further open the door of IPv6 measurement studies by publicly releasing AddrMiner and sharing our data.
AddrMiner naturally works in all announced prefix spaces and enables comprehensive active IPv6 address probing in different scenarios by corresponding algorithms to gradually discover active IPv6 addresses from scratch, from few to many.
Contributions. We make the following contributions:
• We present an active IPv6 address probing method, AddrMiner-N . It fills the gap of address probing in the seedless address space regions and discovers active IPv6 addresses covering 86.4K prefixes announced by BGP, accounting for 81.6% of all announced prefixes.
• We propose an active IPv6 address probing method, AddrMiner-F , which can further discover active IPv6 addresses in address space regions with few seeds. It can find 70%-150% more active addresses than AddrMiner-N and the state-of-the-art algorithms.
• We present an efficient active IPv6 address probing method, AddrMiner-S , which can efficiently perform active IPv6 address probing in address space regions with sufficient seeds. Compared with state-of-the-art algorithms, the results show AddrMiner-S improves the hit rate of active addresses from 28.9% to 56.3%.
• We originally design and implement a global active IPv6 address probing system and discover 2.1 billion active IPv6 addresses, including 1.7 billion de-aliased active addresses and 0.4 billion aliased addresses, through continuous running AddrMiner for 13 months. The developed code and continuously probed active addresses are made publicly available at: https://github.com/AddrMiner/AddrMiner
In this section, we briefly introduce the background of IPv6 addresses and discuss the characteristics of IPv6 addresses. IPv6 addresses are 128 bits long. IPv6 unicast addresses consist of a global routing prefix, a local subnet identifier, and an interface identifier (IID). We represent IPv6 addresses in a human-readable text format using eight groups of four hexadecimal characters, each group having 16 bits in total, separated by a colon (":"). We refer to each hexadecimal character (corresponding to the four bits
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper3
- 6Sense: Internet-Wide IPv6 Scanning and its Security ApplicationsGrant Williams, Mert Erdemir, Amanda Hsu, Shraddha Bhat 等USENIX Security 2024 · 被引用 27 次
- Censys: A Map of Internet Hosts and ServicesZakir Durumeric, Hudson Clark, Jeff Cody, Elliot Cubit 等SIGCOMM 2025 · 被引用 6 次
- PlanB: Efficient Software IPv6 Lookup with Linearized B+-TreeZhihao Zhang, Lanzheng Liu, Chen Chen, Huiba Li 等NSDI 2026 · 被引用 1 次
它引用的顶会 Paper6
- Measuring HTTPS Adoption on the WebAdrienne Porter Felt, Richard Barnes, April King, Chris Palmer 等USENIX Security 2017 · 被引用 177 次
- LZR: Identifying Unexpected Internet ServicesLiz Izhikevich, Renata Teixeira, Zakir DurumericUSENIX Security 2021 · 被引用 63 次
- 6GAN: IPv6 Multi-Pattern Target Generation via Generative Adversarial Nets with Reinforcement LearningTianyu Cui, Gaopeng Gou, Gang Xiong, Chang Liu 等INFOCOM 2021 · 被引用 59 次
- Diamond-Miner: Comprehensive Discovery of the Internet's Topology DiamondsKevin Vermeulen, Justin P. Rohrer, Robert Beverly, Olivier Fourmaux 等NSDI 2020 · 被引用 52 次
- Enumerating Active IPv6 Hosts for Large-Scale Security Scans via DNSSEC-Signed Reverse ZonesKevin Borgolte, Shuang Hao, Tobias Fiebig, Giovanni VignaS&P 2018 · 被引用 48 次
相关 Paper
- Breaking the Seed Barrier: Discovering Active IPv6 Addresses in Seedless ScenariosWenjian Zhang, Guanglei Song, Binkai Ma, Lin He 等INFOCOM 2026
- 6Hit: A Reinforcement Learning-based Approach to Target Generation for Internet-wide IPv6 ScanningBingnan Hou, Zhiping Cai, Kui Wu, Jinshu Su 等INFOCOM 2021 · 被引用 75 次
- Search in the Expanse: Towards Active and Global IPv6 HitlistsBingnan Hou, Zhiping Cai, Kui Wu, Tao Yang 等INFOCOM 2023 · 被引用 27 次
- Pruning as Scanning: Towards Internet-Wide IPv6 Network Periphery DiscoveryTao Yang, Ling Hu, Bingnan Hou, Zhenzhong Yang 等INFOCOM 2025 · 被引用 7 次
- IPv6 Prefix Target Generation through Pattern and Distribution Learning using Vision-Transformer and Guided-DiffusionYaochen Ren, Gaopeng Gou, Chengshang Hou, Tianyu Cui 等INFOCOM 2025 · 被引用 7 次
