How dynamic is the ISPs address space? Towards internet-wide DHCP churn estimation

Moura, Giovane C. M.; Gañán, Carlos; Lone, Qasim; Poursaied, Payam; Asghari, Hadi; Eeten, Michel van

doi:10.1109/ifipnetworking.2015.7145335

Cited by 28 publications

(6 citation statements)

References 27 publications

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“…Work [4] dealt with the relation of IP addresses and hosts with a focus on how ISPs organise their address space. Active measurements (interpolation of the timestamps of acknowledgement messages) were carried out to estimate how long the hosts kept the same IP address.…”

Section: Related Workmentioning

confidence: 99%

Survival Analysis and Prediction Model of IP Address Assignment Duration

Komosný

Rehman

2020

IEEE Access

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IP addresses of end hosts change when they are reassigned. We apply survival analysis, which is commonly used in healthcare, on IP addresses to predict their assignment duration (their lifetime). We propose a survival parametric model based on a history of 6 years of address assignments on a worldwide scale. Our model outperforms alternative models both from short-term and long-term views. The custom modelling is also discussed as address assignment varies across Internet service providers (ISPs) and autonomous systems (ASs). A predictable address assignment duration has many applications, including source reputation, topology mapping, and geolocation. We describe a use-case in fraud prevention, where the proposed model is used as a trigger for two-factor authentication. The created dataset of addresses assignment durations is made publicly available.

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Section: Related Workmentioning

confidence: 99%

Survival Analysis and Prediction Model of IP Address Assignment Duration

Komosný

Rehman

2020

IEEE Access

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“…(1) Computationally scalable: Predicting services across all ports and IP addresses encompasses a large search space, but requires a solution that operates in a constrained amount of wall-time. This is especially important as Internet services are constantly changing [34]. For example, we conduct a scan of the same 0.1% of the IPv4 address space across 65K ports on June 17, 2021 and June 27, 2021.…”

Section: Normalized Servicesmentioning

confidence: 99%

Predicting IPv4 services across all ports

Izhikevich

Teixeira

Durumeric

2022

Proceedings of the ACM SIGCOMM 2022 Conference

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Internet-wide scanning is commonly used to understand the topology and security of the Internet. However, IPv4 Internet scans have been limited to scanning only a subset of services-exhaustively scanning all IPv4 services is too costly and no existing bandwidthsaving frameworks are designed to scan IPv4 addresses across all ports. In this work we introduce GPS, a system that efficiently discovers Internet services across all ports. GPS runs a predictive framework that learns from extremely small sample sizes and is highly parallelizable, allowing it to quickly find patterns between services across all 65K ports and a myriad of features. GPS computes service predictions in 13 minutes (four orders of magnitude faster than prior work) and finds 92.5% of services across all ports with 131× less bandwidth, and 204× more precision, compared to exhaustive scanning. GPS is the first work to show that, given at least two responsive IP addresses on a port to train from, predicting the majority of services across all ports is possible and practical.

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“…Moura et al [20] repeatedly pinged 1 million IP addresses of one ISP to estimate the churn caused by dynamic IP addressing. They compared the ping data with ground truth provided by the ISP and report the accuracy of their churn estimation to be 70%.…”

Section: Ip Space Estimationmentioning

confidence: 99%

Collaborative and privacy-preserving estimation of IP address space utilisation

2017

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Exhaustion of the IPv4 address space is driving mitigation technologies, such as carriergrade NAT or IPv6. Understanding this driver requires knowing how much allocated IPv4 space is actively used over time-a non-trivial goal due to privacy concerns and practical measurement challenges. To address this gap we present a collaborative and privacy-preserving capture-recapture (CR) technique for estimating IP address space utilisation. Public and private datasets of IP addresses observed by multiple independent collaborators can be combined for CR analysis, without any individual collaborator's privately observed addresses leaking to the others. We show that CR estimation is much more accurate than assuming all used addresses are observed, and that our scheme scales well to datasets of over a billion addresses across several collaborators. We estimate that 1.2 billion IPv4 addresses and 6.5 million /24 subnets were actively used at the end of 2014, and also analyse address usage depending on RIR and country.

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How dynamic is the ISPs address space? Towards internet-wide DHCP churn estimation

Cited by 28 publications

References 27 publications

Survival Analysis and Prediction Model of IP Address Assignment Duration

Survival Analysis and Prediction Model of IP Address Assignment Duration

Predicting IPv4 services across all ports

Collaborative and privacy-preserving estimation of IP address space utilisation

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