APPLE: Alias Pruning by Path Length Estimation

Marder, Alexander

doi:10.1007/978-3-030-44081-7_15

Cited by 9 publications

(7 citation statements)

References 23 publications

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“…In this paper, we investigated two research questions: (i) what is the hardware ecosystem in the Internet and operators and (ii) what could happen if an attacker can easily identify router brands and target specific vendor with (known) security breaches? For this analysis, we rely on an updated dataset and make use of a novel alias resolution technique, Apple [25], to refine our view of the operators' networks.…”

Section: Discussionmentioning

confidence: 99%

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Targeted Attack through Network Fingerprinting

Marechal

Donnet

2021

JCSANDM

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Nowadays, simple tools such as traceroute can be used by attackers to acquire topology knowledge remotely. Worse still, attackers can use a lightweight fingerprinting technique, based on traceroute and ping, to retrieve the routers brand, and use that knowledge to launch targeted attacks. In this paper, we show that the hardware ecosystem of network operators can greatly vary from one to another, with all potential security implications it brings. Indeed, depending on the autonomous system (AS), not all brands play the same role in terms of network connectivity and network usage (MPLS vs. standard traffic). An attacker could find an interest in targeting a specific hardware vendor in a particular AS, if known defects are present in this hardware, and if the AS relies heavily on it for forwarding its traffic.

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Section: Discussionmentioning

confidence: 99%

“…Additionally, we used Apple [25], a new technique for resolving router IP aliases that complements existing techniques, such as MIDAR. Apple was able to find 26,808 routers involving 87,492 addresses.…”

Section: Data Collectionmentioning

confidence: 99%

Targeted Attack through Network Fingerprinting

Marechal

Donnet

2021

JCSANDM

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“…Out of the 900k addresses discovered by TNT, Midar found 45,977 routers involving 147,633 addresses. Additionally, we used Apple [28] (between May 10 th , 2021 and May 12 th , 2021), a technique for resolving router IP aliases that complements existing techniques, such as Midar. We deployed Apple on EdgeNet [39], a Kubernetes cluster dedicated to network and distributed systems research, and were able to find 26,729 routers involving 87,532 addresses.…”

Section: Datasetmentioning

confidence: 99%

“…5.5), in which Anaximander will send probes based on the target list, taking advantage of the scheduling of the targets to speed up the discovery progression and possibly stop the probing in some portions when the discovery becomes marginal in said portions. Once IP interfaces have been collected, Anaximander can run alias resolution for generating a router-level map of the ISP, using for instance the combination of Midar [22] and Apple [28].…”

Section: Anaximandermentioning

confidence: 99%

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ISP Probing Reduction with Anaximander

Marechal

Mérindol

Donnet

2022

Passive and Active Measurement

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Since the early 2000's, Internet topology discovery has been an active research topic, providing data for various studies such as Internet modeling, network management, or to assist and support network protocol design. Within this research area, ISP mapping at the router level has attracted little interest despite its utility to perform intra-domain routing evaluation. Since Rocketfuel (and, to a smaller extent, mrinfo), no new tool or method has emerged for systematically mapping intra-domain topologies. In this paper, we introduce Anaximander, a new efficient approach for probing and discovering a targeted ISP in particular. Considering a given set of vantage points, we implement and combine several predictive strategies to mitigate the number of probes to be sent without sacrificing the ISP coverage. To assess the ability of our method to efficiently retrieve an ISP map, we rely on a large dataset of ISPs having distinct nature and demonstrate how Anaximander can be tuned with a simple parameter to control the trade-off between coverage and probing budget.

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Unconsidered Installations: Discovering IoT Deployments in the IPv6 Internet

Dahlmanns,

Heidenreich,

Lohmöller

et al. 2024

NOMS 2024-2024 IEEE Network Operations and Management Symposium

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Internet-wide studies provide extremely valuable insight into how operators manage their Internet of Things (IoT) deployments in reality and often reveal grievances, e.g., significant security issues. However, while IoT devices often use IPv6, past studies resorted to comprehensively scan the IPv4 address space. To fully understand how the IoT and all its services and devices is operated, including IPv6-reachable deployments is inevitablealthough scanning the entire IPv6 address space is infeasible.In this paper, we close this gap and examine how to discover IPv6-reachable IoT deployments. Using three sources of active IPv6 addresses and eleven address generators, we discovered 6658 IoT deployments. We derive that the available address sources are a good starting point for finding IoT deployments. Additionally, we show that using two address generators is sufficient to cover most found deployments. Assessing the security of the deployments, we surprisingly find similar issues as in the IPv4 Internet, although IPv6 deployments might be newer and generally more up-to-date: Only 39 % of deployments have access control in place and only 6.2 % make use of TLS inviting attackers, e.g., to eavesdrop sensitive data.

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APPLE: Alias Pruning by Path Length Estimation

Cited by 9 publications

References 23 publications

Targeted Attack through Network Fingerprinting

Targeted Attack through Network Fingerprinting

ISP Probing Reduction with Anaximander

Unconsidered Installations: Discovering IoT Deployments in the IPv6 Internet

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