Entropy/IP: Uncovering Structure in IPv6 Addresses
| Autor: | Arthur W. Berger, Paweł Foremski, David Plonka |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Networking and Internet Architecture (cs.NI)
FOS: Computer and information sciences IPv6 address Computer science Computer Science - Artificial Intelligence Information Theory (cs.IT) Computer Science - Information Theory Bayesian network 020206 networking & telecommunications 02 engineering and technology computer.software_genre IPv6 Identifier Prefix Computer Science - Networking and Internet Architecture Artificial Intelligence (cs.AI) 0202 electrical engineering electronic engineering information engineering Entropy (information theory) A priori and a posteriori 020201 artificial intelligence & image processing Data mining computer Active networking |
| Zdroj: | Internet Measurement Conference |
| Popis: | In this paper, we introduce Entropy/IP: a system that discovers Internet address structure based on analyses of a subset of IPv6 addresses known to be active, i.e., training data, gleaned by readily available passive and active means. The system is completely automated and employs a combination of information-theoretic and machine learning techniques to probabilistically model IPv6 addresses. We present results showing that our system is effective in exposing structural characteristics of portions of the IPv6 Internet address space populated by active client, service, and router addresses. In addition to visualizing the address structure for exploration, the system uses its models to generate candidate target addresses for scanning. For each of 15 evaluated datasets, we train on 1K addresses and generate 1M candidates for scanning. We achieve some success in 14 datasets, finding up to 40% of the generated addresses to be active. In 11 of these datasets, we find active network identifiers (e.g., /64 prefixes or `subnets') not seen in training. Thus, we provide the first evidence that it is practical to discover subnets and hosts by scanning probabilistically selected areas of the IPv6 address space not known to contain active hosts a priori. Paper presented at the ACM IMC 2016 in Santa Monica, USA (https://dl.acm.org/citation.cfm?id=2987445). Live Demo site available at http://www.entropy-ip.com/ |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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