Resolving the Tussle in the Internet: Mapping, Architecture, and Policy Making

Project Information

ResolutioNet

Grant agreement ID: 679158

DOI

10.3030/679158

Project closed

EC signature date 28 June 2016

Start date 1 February 2017

End date 31 January 2023

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 1 499 875,00

EU contribution

€ 1 499 875,00

Coordinated by

TECHNISCHE UNIVERSITEIT DELFT
Netherlands

Periodic Reporting for period 4 - ResolutioNet (Resolving the Tussle in the Internet: Mapping, Architecture, and Policy Making)

Reporting period: 2021-07-01 to 2023-01-31

Summary of the context and overall objectives of the project

The Internet is the digital backbone of our modern civilization and economy. It has evolved to be the de-facto platform for communication, commerce, and social development. Indeed, thanks to the Internet innovation and access to knowledge have flourished because it lowers the entry burden for anyone to be a global citizen and for any company to have a global presence. However, the Internet was not designed and operated by one entity, but it evolves as an interaction of thousands of networks with diverse and often conflicting objectives. The contention among the various stakeholders leads to negative externalities that affect the user experience and the development of the Internet.

This project aims: (1) characterize the complex interactions among the various Internet stakeholders using a measurement-driven approach, (2) design and develop network systems to resolve conflicts among various Internet stakeholders , (3) enable collaborative network architectures to reach a win-win situation for all the involved parties, (4) understand cyber-threats, and (5) inform policy making about the state and health of the Internet and suggest policies to incentivize cooperation,

The project challenges our mental model about the operation and structure of the Internet. A better understanding of the Internet that this project offers will contribute to ongoing regulatory, educational, and industrial efforts towards a faster and more accessible Internet. We expect that the methodologies, tools, and results derived in this project will be material for future computer networking textbooks, but also be of great value for scientists in other scientific fields that model the Internet such as distributed systems, mathematics, political science, and economics. We also study cyberthreats and develop techniques to protect the Internet and Web.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The work performed in the ResolutioNet project contributes to many topics in Computer Networking, Security, and Policy.

Regarding Internet sustainability, we performed a data-driven analysis and system design towards a more sustainable Internet in light of the ever-increasing traffic demand and competitiveness in the Internet ecosystem. We developed and evaluated algorithms for incremental and sustainable upgrades of ISP networks [Transactions on Networking 2019, INFOCOM 2017] and datacenters [ANCS 2021], and performed a multi-discipline analysis of the forces that shape Internet content delivery [SIGCOMM 2021, HotNets 2021, Telecom Policy Journal 2017] and the Network Neutrality debate [CCR 2020]. We developed and operated a novel system [CoNEXT 2019] to enable the collaboration between network providers and content network providers. We also we developed techniques for geo-distributed analytic techniques [TNSM 2022] and summarized our experience and best practices for reproducibility [CCR 2019].

We studied and defended online user privacy. We performed a large-scale study to assess the compliance of ad and tracking services with the recently implemented European Union General Data Protection Regulation (GDPR), concerning the physical location of the servers and the sensitive topics that they track [IMC2018 on GDPR compliance assessment]. We also developed classifiers to identify sensitive Websites in the Web [IMC2020 on GDPR classifiers] and performed a large-scale study to assess what extent persistent cookies and trackers are present in governmental, international organisations, and COVID-19 information websites [WebSci 2022]. We also developed secure Federated Learning methods for robust classification of GDPR-related sensitive and general topics [NDSS2023]. In a parallel effort, we investigated privacy and security vulnerabilities of Internet of Things (IoT) [IMC 2022, IMC2020 on IoT detection] and IPv6 [CCR 2022].

With regards to Internet security and cyberthreats, we investigated and analyzed cyber threats towards understanding the dark web economy [IEEEAccess 2023] and mitigating cyberattacks [CACM 2023]. We also developed algorithms and techniques to detect and analyze critical Internet infrastructure failures [SIGCOMM 2017,CoNEXT 2021] and the Internet's behavior under stress [CACM 2021,IMC 2020 on COVID19, Book chapter on COVID-19, TMA 2023] towards understanding and mitigating evolving threats in an increasingly complex Internet ecosystem. We also inferred attack mitigation strategies by Internet stakeholders [IMC 2017] and efficiently mitigated Tbps-level using collaborative architectures that involve Internet infrastructure and peering providers [CCS 2021, CoNEXT 2018]. In the process, we uncovered vulnerabilities in the global routing system [IMC2018 on BGP Communities Attacks, CoNEXT 2020, IMC2021 on BGP Communities]. We investigated the propagation of software updates in end-user devices such as smartphones [IMC2020 on software updates], and studied security issues of deployed routers [IMC2021 on SNMPv3 protocol] and programmable networks [Transactions on Networking 2023, INFOCOM 2021].

Papers that report on results of the ResolutioNet project have been awarded:
(1) "One Step at a Time: Optimizing SDN Upgrades in ISP Networks", IEEE INFOCOM 2017, [Best paper award, Fast-track to IEEE/ACM Transactions on Networking],
(2) "Tracing Cross Border Web Tracking", ACM IMC 2018 [Distinguished paper award],
(3) "BGP Communities: Even more Worms in the Routing Can", ACM IMC 2018 [IETF/IRTF Applied Networking Research Prize 2019],
(4) "The Dagstuhl Beginners Guide to Reproducibility for Experimental Networking Research", ACM SIGCOMM Computer Communication Review [Best of CCR in 2019],
(5) "Steering Hyper-Giants' Traffic at Scale", ACM CoNEXT 2019 [Best Paper award and IETF/IRTF Applied Networking Research Prize 2020],
(6) "A Year in Lockdown: How the Waves of COVID-19 Impact Internet Traffic", Communications of the ACM appeared [CACM Research Highlights],
(7) "Seven Years in the Life of Hypergiants' Off-Nets", ACM SIGCOMM 2021, [Best paper award],
(8) "United We Stand: Collaborative Detection and Mitigation of Amplification DDoS Attacks at Scale", ACM CCS 2021 [IETF/IRTF Applied Networking Research Prize 2022]


All the publications, dissemination efforts (including keynotes, invited talks, etc.), and released datasets and software are available in the research webpage of the project:
https://gsmaragd.github.io/research/ResolutioNet/

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

ResolutioNet has significantly advanced our understanding of the cooperation level and the complex interactions among Internet stakeholders at the core of the Internet. During the first part of the project the focus was on the understanding of the Internet evolution. Particular attention was given on the interactions and traffic shaping due to edge servers and end-user devices, e.g. smartphones and home devices. We were also interested in understanding the privacy and regulatory implications of an Internet that expands at the edges, and investigate the new tussles that arise at all layers from the network layer up to the application layer.In the second part of the project the focus turned into the security and privacy aspects of the Internet and the Web, as well as the measurement and understanding of cyberthreats. We developed data-driven techniques to infer network vulnerabilities, shed light to malware attacks and ransom laundry techniques, and attacks to federated systems.

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