Towards a traffic map of the Internet Connecting the dots between popular services and users: Connecting the dots between popular services and users

The impact of Internet phenomena depends on how they impact users, but researchers lack visibility into how to translate Internet events into their impact. Distressingly, the research community seems to have lost hope of obtaining this information without relying on privileged viewpoints. We argue for optimism thanks to new network measurement methods and changes in Internet structure which make it possible to construct an "Internet traffic map". This map would identify the locations of users and major services, the paths between them, and the relative activity levels routed along these paths. We sketch our vision for the map, detail new measurement ideas for map construction, and identify key challenges that the research community should tackle. The realization of an Internet traffic map will be an Internet-scale research effort with Internet-scale impacts that reach far beyond the research community, and so we hope our fellow researchers are excited to join us in addressing this challenge

A view of Internet Traffic Shifts at {ISP} and {IXPs} during the {COVID}-19 Pandemic

Due to the COVID-19 pandemic, many governments imposed lockdowns that forced hundreds of millions of citizens to stay at home. The implementation of confinement measures increased Internet traffic demands of residential users, in particular, for remote working, entertainment, commerce, and education, which, as a result, caused traffic shifts in the Internet core. In this paper, using data from a diverse set of vantage points (one ISP, three IXPs, and one metropolitan educational network), we examine the effect of these lockdowns on traffic shifts. We find that the traffic volume increased by 15-20% almost within a week – while overall still modest, this constitutes a large increase within this short time period. However, despite this surge, we observe that the Internet infrastructure is able to handle the new volume, as most traffic shifts occur outside of traditional peak hours. When looking directly at the traffic sources, it turns out that, while hypergiants still contribute a significant fraction of traffic, we see (1) a higher increase in traffic of non-hypergiants, and (2) traffic increases in applications that people use when at home, such as Web conferencing, VPN, and gaming. While many networks see increased traffic demands, in particular, those providing services to residential users, academic networks experience major overall decreases. Yet, in these networks, we can observe substantial increases when considering applications associated to remote working and lecturing.EC/H2020/679158/EU/Resolving the Tussle in the Internet: Mapping, Architecture, and Policy Making/ResolutioNe

The Adblocking Tug-of-War

Online advertising subsidizes a majority of the “free” services on the Web. Yet many find this approach intrusive and annoying, resorting to adblockers to get rid of ads chasing them all over the Web. A majority of those using an adblocker tool are familiar with messages asking them to either disable their adblocker or to consider supporting the host Web site via a donation or subscription. This is a recent development in the ongoing adblocking arms race which we have explored in our recent report, “Adblocking and Counter Blocking: A Slice of the Arms Race”. For our study, we used popular adblockers, trawled the Web and analyzed some of the most popular sites to uncover how many are using anti-adblockers. Our preliminary analysis found that anti-adblockers come from a small number of providers, are widely used, and that adblockers also often block anti-adblockers

O discurso dos #ProtestosBR: análise de conteúdo do Twitter

This paper focus on an analysis of the discourse of Twitter messages during the protests in Brazil during June 2013. Our objective is to discuss how the concepts relate to each other and form networks of meanings around the tweets about the protests. Our search for common characteristics and elements reveals how Twitter was used to describe the protests and to mobilize people rather than to discuss what was actually taking place. We describe the key actors, contexts and demands, as well as the focus on live narratives, #pamphleteer hashtags, and the specific location of tweets

Adaptive data acquisition strategies for energy-efficient, smartphone-based, continuous processing of sensor streams

Ministry of Education, Singapore under its Academic Research Funding Tier

Identifying Sensitive URLs at Web-Scale

Several data protection laws include special provisions for protecting personal data relating to religion, health, sexual orientation, and other sensitive categories. Having a well-defined list of sensitive categories is sufficient for filing complaints manually, conducting investigations, and prosecuting cases in courts of law. Data protection laws, however, do not define explicitly what type of content falls under each sensitive category. Therefore, it is unclear how to implement proactive measures such as informing users, blocking trackers, and filing complaints automatically when users visit sensitive domains. To empower such use cases we turn to the Curlie.org crowdsourced taxonomy project for drawing training data to build a text classifier for sensitive URLs. We demonstrate that our classifier can identify sensitive URLs with accuracy above 88%, and even recognize specific sensitive categories with accuracy above 90%. We then use our classifier to search for sensitive URLs in a corpus of 1 Billion URLs collected by the Common Crawl project. We identify more than 155 millions sensitive URLs in more than 4 million domains. Despite their sensitive nature, more than 30% of these URLs belong to domains that fail to use HTTPS. Also, in sensitive web pages with third-party cookies, 87% of the third-parties set at least one persistent cookie