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network outages in Louisiana with Hurricane Ida

We’ve been watching the situation in Louisiana develop with Hurricane Ida with our Trinocular Internet outage detection system.

Internet outages in Louisiana at 8:30pm Sunday evening August 29, corresponding to Hurricane Ida’s landfall.

Data as of 2021-08-30t01:30Z, which is 8:30pm Sunday night August 29 in New Orleans, shows about half of the networks in the New Orleans area being unreachable (mostly IPv4 home networks). Following shortly after landfall, these outages correspond with news reports about widespread power loss. Current data is appearing on our Internet outage map.

We wish the residents of Louisiana the best and hope for a rapid recovery.

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Uncategorized

ANT research group lunch

At the end of June we had an ANT research group lunch to celebrate four (!) recent PhD defenses in 2020 and 2021: Hang Guo, Calvin Ardi, Lan Wei, and Abdul Qadeer. Although not everyone could be there (Hang has already moved for his new job), and the ANT lab includes a number of people outside of L.A. who could not make it, us students, staff, and family in L.A. had a great time at Vista del Mar Park near the beach!

A big thanks to Basileal Imana and ASM Rizvi for coordinating delivery of Ethiopian food for lunch.

We are also very thankful that vaccine availability in the U.S. is widespread and we were able to get together face-to-face after a year of Covid limitations. I’m happy that we’ve been able to do good work throughout the pandemic with remote collaboration tools and occasional on-site access, but it was nice to see old friends face-to-face again and share a meal. We hope the fall’s in-person classes at USC go well.

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Uncategorized

new talk “Observing the Global IPv4 Internet: What IP Addresses Show” as an SKC Science and Technology Webinar

John Heidemann gave the talk “Observing the Global IPv4 Internet: What IP Addresses Show” at the SKC Science and Technology Webinar, hosted by Deepankar Medhi (U. Missouri-Kansas City and NSF) on June 18, 2021.  A video of the talk is on YouTube at https://www.youtube.com/watch?v=4A_gFXi2WeY. Slides are available at https://www.isi.edu/~johnh/PAPERS/Heidemann21a.pdf.

From the abstract:Covid and non-Covid network changes in India; part of a talk about measuring the IPv4 Internet.

Since 2014 the ANT lab at USC has been observing the visible IPv4 Internet (currently 5 million networks measured every 11 minutes) to detect network outages. This talk explores how we use this large-scale, active measurement to estimate Internet reliability and understand the effects of real-world events such as hurricanes. We have recently developed new algorithms to identify Covid-19-related Work-from-Home and other Internet shutdowns in this data. Our Internet outage work is joint work of John Heidemann, Lin Quan, Yuri Pradkin, Guillermo Baltra, Xiao Song, and Asma Enayet with contributions from Ryan Bogutz, Dominik Staros, Abdulla Alwabel, and Aqib Nisar.

This project is joint work of a number of people listed in the abstract above, and is supported by NSF 2028279 (MINCEQ) and CNS-2007106 (EIEIO). All data from this paper is available at no cost to researchers.

Categories
Data Papers Publications

New paper “Auditing for Discrimination in Algorithms Delivering Job Ads” at TheWebConf 2021

We published a new paper “Auditing for Discrimination in Algorithms Delivering Job Ads” by Basileal Imana (University of Southern California), Aleksandra Korolova (University of Southern California) and John Heidemann (University of Southern California/ISI) at TheWebConf 2021 (WWW ’21).

From the abstract:

Skew in the delivery of real-world ads on Facebook (FB) but not LinkedIn (LI).
Comparison of ad delivery using “Reach” (R) and “Conversion” (C) campaign objectives on Facebook. There is skew for both cases but less skew for “Reach”.

Ad platforms such as Facebook, Google and LinkedIn promise value for advertisers through their targeted advertising. However, multiple studies have shown that ad delivery on such platforms can be skewed by gender or race due to hidden algorithmic optimization by the platforms, even when not requested by the advertisers. Building on prior work measuring skew in ad delivery, we develop a new methodology for black-box auditing of algorithms for discrimination in the delivery of job advertisements. Our first contribution is to identify the distinction between skew in ad delivery due to protected categories such as gender or race, from skew due to differences in qualification among people in the targeted audience. This distinction is important in U.S. law, where ads may be targeted based on qualifications, but not on protected categories. Second, we develop an auditing methodology that distinguishes between skew explainable by differences in qualifications from other factors, such as the ad platform’s optimization for engagement or training its algorithms on biased data. Our method controls for job qualification by comparing ad delivery of two concurrent ads for similar jobs, but for a pair of companies with different de facto gender distributions of employees. We describe the careful statistical tests that establish evidence of non-qualification skew in the results. Third, we apply our proposed methodology to two prominent targeted advertising platforms for job ads: Facebook and LinkedIn. We confirm skew by gender in ad delivery on Facebook, and show that it cannot be justified by differences in qualifications. We fail to find skew in ad delivery on LinkedIn. Finally, we suggest improvements to ad platform practices that could make external auditing of their algorithms in the public interest more feasible and accurate.

This paper was awarded runner-up for best student paper at The Web Conference 2021.

The data from this paper is upon request, please see our dataset page.

This work was reported in the popular press: The InterceptMIT Technology ReviewWall Street JournalThe RegisterVentureBeatReutersThe VergeEngadgetAssociated Press.

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Announcements Projects

new project “Measuring the Internet during Novel Coronavirus to Evaluate Quarantine” (MINCEQ)

We are happy to announce a new project “Measuring the Internet during Novel Coronavirus to Evaluate Quarantine” (MINCEQ).

Measuring the Internet during Novel Coronavirus to Evaluate Quarantine (RAPID-MINCEQ) is a project to measure changes in Internet use during the COVID-19 outbreak of 2020. As the world grapples with COVID-19, work-from-home and study-from-home are widely employed. Implementation of these policies varies across the U.S. and globally due to local circumstances. A common consequence is a huge shift in Internet use, with schools and workplaces emptying and home Internet use increasing. The goal of this project is to observe this shift, globally, through changes in Internet address usage, allowing observation of early reactions to COVID and, one hopes, a future shift back.

This project plans to develop two complementary methods of assessing Internet use by measuring address activity and how it changes relative to historical trends. The project will directly measure Internet address use globally based on continuous, ongoing measurements of more than 4 million IPv4 networks. The project will also directly measure Internet address use in network traffic at a regional Internet exchange point where multiple Internet providers interconnect. The first approach provides a global picture, while the second provides a more detailed but regional picture; together they will help evaluate measurement accuracy.

The project website is at https://ant.isi.edu/minceq/index.html. The PI is John Heidemann. This work is supported by NSF as a RAPID award in response to COVID-19, award NSF-2028279.

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Social

group lunch in honor of a departure and two arrivals

On November 14 we had a group lunch near ISI to celebrate the completion of Joao Ceron’s visit from the University of Twente as a visiting scholar, to welcome Asma Enayet to the group as a new PhD student, and to welcome Hang Guo’s son into the world. (Hang was understandably not able to make the lunch.) Happy Thanksgiving to all!

A group lunch in honor of Asma (left) and Joao (6th left).
Categories
Publications Technical Report

new technical report “Improving the Optics of Active Outage Detection (extended)”

We have released a new technical report “Improving the Optics of the Active Outage Detection (extended)”, by Guillermo Baltra and John Heidemann, as ISI-TR-733.

From the abstract:

A sample block showing changes in block usage (c), and outage detection results of Trinocular (b) and improved with the Full Block Scanning Algorithm (a).

There is a growing interest in carefully observing the reliability of the Internet’s edge. Outage information can inform our understanding of Internet reliability and planning, and it can help guide operations. Outage detection algorithms using active probing from third parties have been shown to be accurate for most of the Internet, but inaccurate for blocks that are sparsely occupied. Our contributions include a definition of outages, which we use to determine how many independent observers are required to determine global outages. We propose a new Full Block Scanning (FBS) algorithm that gathers more information for sparse blocks to reduce false outage reports. We also propose ISP Availability Sensing (IAS) to detect maintenance activity using only external information. We study a year of outage data and show that FBS has a True Positive Rate of 86%, and show that IAS detects maintenance events in a large U.S. ISP.

All data from this paper will be publicly available.

Categories
Presentations

Talks at DNS-OARC 61

Wes Hardaker gave two presentations at DNS-OARC on November 1st, 2019. The first was a presentation about the previously announced “Cache me if you can” paper, which is on youtube, and the slides are available as well. The second talk presented Haoyu Jiang’s work during the summer of 2018 on analyzing DNS B-Root traffic during the 2018 DITL data for levels of traffic sent by the Chrome web browser, levels of traffic associated with different languages, and levels of traffic sent by different label lengths. It is available on youtube with the slides here.

Categories
Announcements

reblogging: the diurnal Internet and DNS backscatter

We are happy to share that two of our older topics have appeared more recently in other venues.

Our animations of the diurnal Internet, originally seen in our 2014 ACM IMC paper and our blog posts, was noticed by Gerald Smith who used it to start a discussion with seventh-grade classes in Mahe, India and (I think) Indiana, USA as part of his Fullbright work. It’s great to see research work that useful to middle-schoolers!

Kensuke Fukuda recently posted about our work on identifying IPv6 scanning with DNS backscatter at the APNIC blog. This work was originally published at the 2018 ACM IMC and posted in our blog. It’s great to see that work get out to a new audience.

Categories
Papers Publications

new paper “Precise Detection of Content Reuse in the Web” to appear in ACM SIGCOMM Computer Communication Review

We have published a new paper “Precise Detection of Content Reuse in the Web” by Calvin Ardi and John Heidemann, in the ACM SIGCOMM Computer Communication Review (Volume 49 Issue 2, April 2019) newsletter.

From the abstract:

With vast amount of content online, it is not surprising that unscrupulous entities “borrow” from the web to provide content for advertisements, link farms, and spam. Our insight is that cryptographic hashing and fingerprinting can efficiently identify content reuse for web-size corpora. We develop two related algorithms, one to automatically discover previously unknown duplicate content in the web, and the second to precisely detect copies of discovered or manually identified content. We show that bad neighborhoods, clusters of pages where copied content is frequent, help identify copying in the web. We verify our algorithm and its choices with controlled experiments over three web datasets: Common Crawl (2009/10), GeoCities (1990s–2000s), and a phishing corpus (2014). We show that our use of cryptographic hashing is much more precise than alternatives such as locality-sensitive hashing, avoiding the thousands of false-positives that would otherwise occur. We apply our approach in three systems: discovering and detecting duplicated content in the web, searching explicitly for copies of Wikipedia in the web, and detecting phishing sites in a web browser. We show that general copying in the web is often benign (for example, templates), but 6–11% are commercial or possibly commercial. Most copies of Wikipedia (86%) are commercialized (link farming or advertisements). For phishing, we focus on PayPal, detecting 59% of PayPal-phish even without taking on intentional cloaking.