Categories
Announcements Outages

new website for browsing Internet outages

We are happy to announce a new website at https://ant.isi.edu/outage/world/ that supports our Internet outage data collected from Trinocular.

The ANT Outage world browser, showing Hurricane Irma just after landfall in Florida in Sept. 2017.

Our website supports browsing more than two years of outage data, organized by geography and time.  The map is a google-maps-style world map, with circle on it at even intervals (every 0.5 to 2 degrees of latitude and longitude, depending on the zoom level).  Circle sizes show how many /24 network blocks are out in that location, while circle colors show the percentage of outages, from blue (only a few percent) to red (approaching 100%).

We hope that this website makes our outage data more accessible to researchers and the public.

The raw data underlying this website is available on request, see our outage dataset webpage.

The research is funded by the Department of Homeland Security (DHS) Cyber Security Division (through the LACREND and Retro-Future Bridge and Outages projects) and Michael Keston, a real estate entrepreneur and philanthropist (through the Michael Keston Endowment).  Michael Keston helped support this the initial version of this website, and DHS has supported our outage data collection and algorithm development.

The website was developed by Dominik Staros, ISI web developer and owner of Imagine Web Consulting, based on data collected by ISI researcher Yuri Pradkin. It builds on prior work by Pradkin, Heidemann and USC’s Lin Quan in ISI’s Analysis of Network Traffic Lab.

ISI has featured our new website on the ISI news page.

 

Categories
Announcements Projects

new project LACANIC

We are happy to announce a new project, LACANIC, the Los Angeles/Colorado Application and Network Information Community.

The LACANIC project’s goal is to develop datasets to improve Internet security and readability. We distribute these datasets through the DHS IMPACT program.

As part of this work we:

  • provide regular data collection to collect long-term, longitudinal data
  • curate datasets for special events
  • build websites and portals to help make data accessible to casual users
  • develop new measurement approaches

We provide several types of datasets:

  • anonymized packet headers and network flow data, often to document events like distributed denial-of-service (DDoS) attacks and regular traffic
  • Internet censuses and surveys for IPv4 to document address usage
  • Internet hitlists and histories, derived from IPv4 censuses, to support other topology studies
  • application data, like DNS and Internet-of-Things mapping, to document regular traffic and DDoS events
  • and we are developing other datasets

LACANIC allows us to continue some of the data collection we were doing as part of the LACREND project, as well as develop new methods and ways of sharing the data.

LACANIC is a joint effort of the ANT Lab involving USC/ISI (PI: John Heidemann) and Colorado State University (PI: Christos Papadopoulos).

We thank DHS’s Cyber Security Division for their continued support!

 

Categories
In-the-news Internet Outages

Evaluation of Hurricane Harvey’s Effects on the Internet’s Edge

On August 25, 2017 Hurricane Harvey made landfall in south Texas, causing widespread property damage, displacing more than 30,000 people, and costing more than 45 lives (as of 2017-09-01).

We sympathize with those were hurt by this disaster, and hope for swift recovery for the region.

We recently examined the effects of Hurricane Harvey on the area using Trinocular, our internet outage detection system.  Two key results:

Trinocular report on outages in Texas after Hurricane Harvey (on 2017-08-28t03:32Z)

We see that landfall was followed by widespread Internet outages in the Corpus Christi area, with 40% or more home networks dropping off the Internet.

We see that over the following days, network outages grew in the Houston area, with many networks dropping off the Internet. However, the fraction of networks lost in Houston was much smaller than in the Corpus Christi area.

More details are on our Hurricane Harvey web page.  We will update that page as we get more data in.

The dataset including Hurricane Harvey will be internet_outage_adaptive_a29all-20170702 and will be released in October 2017. Until the full data is released, we have a preliminary dataset through August 2017 available on request.

Categories
Presentations

new talk “Digging in to Ground Truth in Network Measurements” at the TMA PhD School 2017

John Heidemann gave the talk “Digging in to Ground Truth in Network Measurements” at the TMA PhD School 2017 in Dublin, Ireland on June 19, 2017.  Slides are available at https://www.isi.edu/~johnh/PAPERS/Heidemann17c.pdf.
From the abstract:

New network measurements are great–you can learn about the whole world! But new network measurements are horrible–are you sure you learn about the world, and not about bugs in your code or approach? New scientific approaches must be tested and ultimately calibrated against ground truth. Yet ground truth about the Internet can be quite difficult—often network operators themselves do not know all the details of their network. This talk will explore the role of ground truth in network measurement: getting it when you can, alternatives when it’s imperfect, and what we learn when none is available.

 

This talk builds on research over the last decade with many people, and the slides include some discussion from the TMA PhD school audience.

Travel to the TMA PhD school was supported by ACM, ISI, and the DHS Retro-Future Bridge and Outages project.

Update 2017-07-05: The TMA folks have posted video of this “Ground Truth” talk to YouTube if you want to relive the glory of a warm afternoon in Dublin.

Categories
Presentations

new talk “Collecting and Visualizing Outages Over the Long Haul” at the AIMS Workshop 2017

John Heidemann gave the talk “Collecting and Visualizing Outages Over the Long Haul” at CAIDA’s Active Internet Measurement (AIMS) Workshop in San Diego, California, USA on March 2, 2017.  Slides are available at http://www.isi.edu/~johnh/PAPERS/Heidemann17b.pdf.
From the abstract:

Unmeasurable blocks over time, a challenge in long-haul outage measurement, from [Alwabel15a]
We have been collecting data about outages in the Internet since Oct. 2014. Our outage detection system, Trinocular, uses active probing from four sites to study about 4 million /24 IPv4 address blocks. Long-duration measurements bring challenges that don’t occur in short observations. Most importantly, our target (“the Internet”) changes as we measure it, as new blocks come on-line, old blocks are reused in different ways, and ISPs observe and sometimes block our traffic. Our measurement platform also sees occasional hardware failures. Visualization can assist detection of these problems, allowing human perception to detect changes in data collection that have not previously been anticipated. This talk will discuss the challenges of long-term outage measurement and describe our new algorithm that scales to support clustering of 4M blocks and 3 months of observations for visualization.
Our visualization is joint work with Yuri Pradkin, and analysis of our long-term outages includes work with Abdulla Alwabel.

This talk draws on work from [Alwabel15a].  Data from this talk is available at https://ant.isi.edu/datasets/outage/, and visualizations can be found at https://ant.isi.edu/outage/browse/.

Categories
Presentations

new animation: the August 2014 Time Warner outage

Global network outages on 2014-08-27 during the Time Warner event in the U.S.
Global network outages on 2014-08-27 during the Time Warner event in the U.S.

On August 27, 2014, Time Warner suffered a network outage that affected about 11 million customers for more than two hours (making national news). We have observing global network outages since December 2013, including this outage.

We recently animated this August Time Warner outage.

We see that the Time Warner outage lasted about two hours and affected a good swath of the United States. We caution that all large network operators have occasional outages–this animation is not intended to complain about Time Warner, but to illustrate the need to have tools that can detect and visualize national-level outages.  It also puts the outage into context: we can see a few other outages in Uruguay, Brazil, and Saudi Arabia.

This analysis uses dataset usc-lander /internet_outage_adaptive_a17all-20140701, available for research use from PREDICT, or by request from us if PREDICT access is not possible.

This animation was first shown at the Dec. 2014 DHS Cyber Security Division R&D Showcase and Technical Workshop as part of the talk “Towards Understanding Internet Reliability” given by John Heidemann. This work was supported by DHS, most recently through the LACREND project.

Categories
Presentations

new animation: a sample of U.S. networks, before and after Hurricane Sandy

In October 2012, Hurricane Sandy made landfall on the U.S. East Coast causing widespread power outages. We were able to see the effects of Hurricane Sandy by analyzing active probing of the Internet. We first reported this work in a technical report and then with more refined analysis in a peer-reviewed paper.

Network outages for a sample of U.s. East Coast networks on the day after Hurricane Sandy made landfall.
Network outages for a sample of U.s. East Coast networks on the day after Hurricane Sandy made landfall.

We recently animated our data showing Hurricane Sandy landfall.

These 4 days before landfall and 7 after show some intersting results: On the day of landfall we see about three-times the number of outages relative to “typical” U.S. networks. Finally, we see it takes about four days to recover back to typical conditions.

This analysis uses dataset usc-lander / internet_address_survey_reprobing_it50j, available for research use from PREDICT, or by request from us if PREDICT access is not possible.

This animation was first shown at the Dec. 2014 DHS Cyber Security Division R&D Showcase and Technical Workshop as part of the talk “Towards Understanding Internet Reliability” given by John Heidemann. This work was supported by DHS, most recently through the LACREND project.

Categories
Presentations

new talk “Internet Populations (Good and Bad): Measurement, Estimation, and Correlation” at the ICERM Workshop on Cybersecurity

John Heidemann gave the talk “Internet Populations (Good and Bad): Measurement, Estimation, and Correlation” at the ICERM Workshop on Cybersecurity at Brown University, Providence, Rhode Island on October 22, 2014. Slides are available at http://www.isi.edu/~johnh/PAPERS/Heidemann14e/.

Can we improve the mathematical tools we use to measure and understand the Internet?
Can we improve the mathematical tools we use to measure and understand the Internet?

From the abstract:

Our research studies the Internet’s public face. Since 2006 we have been taking censuses of the Internet address space (pinging all IPv4 addresses) every 3 months. Since 2012 we have studied network outages and events like Hurricane Sandy, using probes of much of the Internet every 11 minutes. Most recently we have evaluated the diurnal Internet, finding countries where most people turn off their computers at night. Finally, we have looked at network reputation, identifying how spam generation correlates with network location, and others have studies multiple measurements of “network reputation”.

A common theme across this work is one must estimate characteristics of the edge of the Internet in spite of noisy measurements and a underlying changes. One also need to compare and correlate these imperfect measurements with other factors (from GDP to telecommunications policies).

How do these applications relate to the mathematics of census taking and measurement, estimation, and correlation? Are there tools we should be using that we aren’t? Do the properties of the Internet suggest new approaches (for example where rapid full enumeration is possible)? Does correlation and estimates of network “badness” help us improve cybersecurity by treating different parts of the network differently?

Categories
Presentations

new animation “Watching the Internet Sleep”

Does the Internet sleep? Yes, and we have the video!

We have recently put together a video showing 35 days of Internet address usage as observed from Trinocular, our outage detection system.

The Internet sleeps: address use in South America is low (blue) in the early morning, while India is high (red) in afternoon.
The Internet sleeps: address use in South America is low (blue) in the early morning, while India is high (red) in afternoon.

The Internet sleeps: address use in South America is low (blue) in the early morning, while India is high (red) in afternoon.  When we look at address usage over time, we see that some parts of the globe have daily swings of +/-10% to 20% in the number of active addresses. In China, India, eastern Europe and much of South America, the Internet sleeps.

Understanding when the Internet sleeps is important to understand how different country’s network policies affect use, it is part of outage detection, and it is a piece of improving our long-term goal of understanding exactly how big the Internet is.

See http://www.isi.edu/ant/diurnal/ for the video, or read our technical paper “When the Internet Sleeps: Correlating Diurnal Networks With External Factors” by Quan, Heidemann, and Pradkin, to appear at ACM IMC, Nov. 2014.

Datasets (listed here) used in generating this video are available.

This work is partly supported by DHS S&T, Cyber Security division, agreement FA8750-12-2-0344 (under AFRL) and N66001-13-C-3001 (under SPAWAR).  The views contained
herein are those of the authors and do not necessarily represent those of DHS or the U.S. Government.  This work was classified by USC’s IRB as non-human subjects research (IIR00001648).

Categories
Papers Publications

new conference paper “When the Internet Sleeps: Correlating Diurnal Networks With External Factors” in IMC 2014

The paper “When the Internet Sleeps: Correlating Diurnal Networks With External Factors” will appear at ACM Internet Measurements Conference 2014 in Vancouver, Canada (available at http://www.isi.edu/~johnh/PAPERS/Quan14c/ with cite and pdf, or direct pdf).

Predicting longitude from observed diurnal phase ([Quan14c], figure 14c)
Predicting longitude from observed diurnal phase for 287k geolocatable, diurnal blocks ([Quan14c], figure 14c)
From the abstract:

As the Internet matures, policy questions loom larger in its operation. When should an ISP, city, or government invest in infrastructure? How do their policies affect use? In this work, we develop a new approach to evaluate how policies, economic conditions and technology correlates with Internet use around the world. First, we develop an adaptive and accurate approach to estimate block availability, the fraction of active IP addresses in each /24 block over short timescales (every 11 minutes). Our estimator provides a new lens to interpret data taken from existing long-term outage measurements, thus requiring no additional traffic. (If new collection was required, it would be lightweight, since on average, outage detection requires less than 20 probes per hour per /24 block; less than 1% of background radiation.) Second, we show that spectral analysis of this measure can identify diurnal usage: blocks where addresses are regularly used during part of the day and idle in other times. Finally, we analyze data for the entire responsive Internet (3.7M /24 blocks) over 35 days. These global observations show when and where the Internet sleeps—networks are mostly always-on in the US and Western Europe, and diurnal in much of Asia, South America, and Eastern Europe. ANOVA (Analysis of Variance) testing shows that diurnal networks correlate negatively with country GDP and electrical consumption, quantifying that national policies and economics relate to networks.

Citation: Lin Quan, John Heidemann, and Yuri Pradkin. When the Internet Sleeps: Correlating Diurnal Networks With External Factors. In Proceedings of the ACM Internet Measurement Conference, p. to appear. Vancouver, BC, Canada, ACM. November, 2014.

All data in this paper is available to researchers at no cost, and source code to our analysis tools is available on request; see our diurnal datasets webpage.

This work is partly supported by DHS S&T, Cyber Security division, agreement FA8750-12-2-0344 (under AFRL) and N66001-13-C-3001 (under SPAWAR).  The views contained
herein are those of the authors and do not necessarily represent those of DHS or the U.S. Government.  This work was classified by USC’s IRB as non-human subjects research (IIR00001648).