Author Archives: Steve Uhlig

Lessons learned organizing the PAM 2020 virtual conference

Chris Misa, Dennis Guse, Oliver Hohlfeld, Ramakrishnan Durairajan, Anna Sperotto, Alberto Dainotti, Reza Rejaie

Abstract

Due to the COVID-19 pandemic, the organizing committee of the 2020 edition of the Passive and Active Measurement (PAM) conference decided to organize it as a virtual event. Unfortunately, little is known about designing and organizing virtual academic conferences in the networking domain and their impacts on the participants’ experience. In this editorial note, we first provide challenges and rationale for various organizational decisions we made in designing the virtual format of PAM 2020. We then illustrate the key results from a questionnaire-based survey of participants’ experience showing that, while virtual conferences have the potential to broaden participation and strengthen focus on technical content, they face serious challenges in promoting social interactions and broadening the scope of discussions. We conclude with key takeaways, lessons learned, and suggestions for future virtual conferences distilled from this experience.

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Open Educational Resources for Computer Networking

Olivier Bonaventure, Quentin De Coninck, Fabien Duchêne, Anthony Gego, Mathieu Jadin, François Michel, Maxime Piraux, Chantal Poncin, Olivier Tilmans

Abstract

To reflect the importance of network technologies, networking courses are now part of the core materials of Computer Science degrees. We report our experience in jointly developing an open-source ebook for the introductory course, and a series of open educational resources for both the introductory and advanced networking courses. These ensure students actively engage with the course materials, through a hands-on approach; and scale to the larger classrooms and limited teaching staff, by leveraging open-source resources and an automated grading platform to provide feedback. We evaluate the impact of these pedagogical innovations by surveying the students, who indicated that these were helpful for them to master the course materials.

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Using Application Layer Banner Data to Automatically Identify IoT Devices

Talha Javed, Muhammad Haseeb, Muhammad Abdullah, Mobin Javed

Abstract

In this paper, we re-implement a recent work published in Usenix Security 2018: “Acquistional Rule Based Engine for Discovering Internet-of-Things Devices”. The paper introduced an NLP-based engine for automatically identifying the type, vendor, and product of IoT devices given banner data as input. We report on our efforts to reproduce the original implementation of the engine, documenting ambiguities around implementation and evaluation details that we encountered, as well as how we addressed them in our work. We evaluate our implementation on two ground truth datasets, finding that it fails to achieve the accuracy reported by the original authors. Our findings highlight the importance of recent community efforts towards a culture of reproducibility by presenting an example of how ambiguities in a research paper combined with lack of access to the original datasets can significantly affect a faithful re-implementation and evaluation.

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Towards Declarative Self-Adapting Buffer Management

Pavel Chuprikov, Sergey Nikolenko, Kirill Kogan

Abstract

Buffering architectures and policies for their efficient management are one of the core ingredients of network architecture. However, despite strong incentives to experiment with and deploy new policies, opportunities for changing or automatically choosing anything beyond a few parameters in a predefined set of behaviors still remain very limited. We introduce a novel buffer management framework based on machine learning approaches which automatically adapts to traffic conditions changing over time and requires only limited knowledge from network operators about the dynamics and optimality of desired behaviors. We validate and compare various design options with a comprehensive evaluation study.

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Does Domain Name Encryption Increase Users’ Privacy?

Martino Trevisan, Francesca Soro, Idilio Drago, Marco Mellia, Ricardo Morla

Abstract

Knowing domain names associated with traffic allows eavesdroppers to profile users without accessing packet payloads. Encrypting domain names transiting the network is, therefore, a key step to increase network confidentiality. Latest efforts include encrypting the TLS Server Name Indication (eSNI extension) and encrypting DNS traffic, with DNS over HTTPS (DoH) representing a prominent proposal. In this paper, we show that an attacker able to observe users’ traffic relying on plain-text DNS can uncover the domain names of users relying on eSNI or DoH. By relying on large-scale network traces, we show that simplistic features and off-the-shelf machine learning models are sufficient to achieve surprisingly high precision and recall when recovering encrypted domain names. The triviality of the attack calls for further actions to protect privacy, in particular considering transient scenarios in which only a fraction of users will adopt these new privacy-enhancing technologies.

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Tracking the deployment of TLS 1.3 on the Web: A story of experimentation and centralization

Ralph Holz, Jens Hiller, Johanna Amann, Abbas Razaghpanah, Thomas Jost, Narseo Vallina-Rodriguez, Oliver Hohlfeld

Abstract

Transport Layer Security (TLS) 1.3 is a redesign of the Web’s most important security protocol. It was standardized in August 2018 after a four year-long, unprecedented design process involving many cryptographers and industry stakeholders. We use the rare opportunity to track deployment, uptake, and use of a new mission-critical security protocol from the early design phase until well over a year after standardization. For a profound view, we combine and analyze data from active domain scans, passive monitoring of large networks, and a crowd-sourcing effort on Android devices. In contrast to TLS 1.2, where adoption took more than five years and was prompted by severe attacks on previous versions, TLS 1.3 is deployed surprisingly speedily and without security concerns calling for it. Just 15 months after standardization, it is used in about 20% of connections we observe. Deployment on popular domains is at 30% and at about 10% across the com/net/org top-level domains (TLDs). We show that the development and fast deployment of TLS 1.3 is best understood as a story of experimentation and centralization. Very few giant, global actors drive the development. We show that Cloudflare alone brings deployment to sizable numbers and describe how actors like Facebook and Google use their control over both client and server endpoints to experiment with the protocol and ultimately deploy it at scale. This story cannot be captured by a single dataset alone, highlighting the need for multi-perspective studies on Internet evolution.

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An Artifact Evaluation of NDP

Noa Zilberman

Abstract

Artifact badging aims to rank the quality of submitted research artifacts and promote reproducibility. However, artifact badging may not indicate inherent design and evaluation limitations.

This work explores current limits in artifact badging using a performance-based evaluation of the NDP artifact. We evaluate the NDP artifact beyond the Reusable badge’s level, investigating the effect of aspects such as packet size and random-number seed on throughput and flow completion time.

Our evaluation demonstrates that while the NDP artifact is reusable, it is not robust, and we identify architectural, implementation and evaluation limitations.

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An Open Platform to Teach How the Internet Practically Works

Thomas Holterbach, Tobias Bü, Tino Rellstab, Laurent Vanbever

Abstract

Each year at ETH Zurich, around 100 students collectively build and operate their very own Internet infrastructure composed of hundreds of routers and dozens of Autonomous Systems (ASes). Their goal? Enabling Internet-wide connectivity. We find this class-wide project to be invaluable in teaching our students how the Internet infrastructure practically works. Among others, our students have a much deeper understanding of Internet operations alongside their pitfalls. Besides students tend to love the project: clearly the fact that all of them need to cooperate for the entire Internet to work is empowering. In this paper, we describe the overall design of our teaching platform, how we use it, and interesting lessons we have learnt over the years. We also make our platform openly available.

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Workshop on Internet Economics (WIE 2019) report

kc claffy, David Clark

Abstract

On 9-11 December 2019, CAIDA hosted the 10th interdisciplinary Workshop on Internet Economics (WIE) at UC San Diego’s Supercomputer Center. This workshop series provides a forum for researchers, Internet facilities and service providers, technologists, economists, theorists, policymakers, and other stakeholders to exchange views on current and emerging economic and policy debates. This year’s meeting had a narrower focus than in years past, motivated by a new NSF-funded project being launched at CAIDA: KISMET (Knowledge of Internet Structure: Measurement, Epistemology, and Technology). The objective of the KISMET project is to improve the security and resilience of key Internet systems by collecting and curating infrastructure data in a form that facilitates query, integration and analysis. This project is a part of NSF’s new Convergence Accelerator program, which seeks to support fundamental scientific exploration by creating partnerships across public and private sectors to solve problems of national importance.

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Thoughts about Artifact Badging

Noa Zilberman, Andrew W. Moore

Abstract

Reproducibility: the extent to which consistent results are obtained when an experiment is repeated, is important as a means to validate experimental results, promote integrity of research, and accelerate follow up work. Commitment to artifact reviewing and badging seeks to promote reproducibility and rank the quality of submitted artifacts.

However, as illustrated in this issue, the current badging scheme, with its focus upon an artifact being reusable, may not identify limitations of architecture, implementation, or evaluation.

We propose that to improve the insight into artifact reproducibility, the depth and nature of artifact evaluation must move beyond simply considering if an artifact is reusable. Artifact evaluation should consider the methods of that evaluation alongside the varying of inputs to that evaluation. To achieve this, we suggest an extension to the scope of artifact badging, and describe both approaches and best practice arising in other communities. We seek to promote conversation and make a call to action intended to strengthen the scientific method within our domain.

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