Hello!
just wanted to remind you that the regular biweekly pluggable
transports meeting is going to occur tomorrow at 16:00 UTC. Place is
the #tor-dev IRC channel in the OFTC network.
Thanks for your attention!
>From October 24th to 26th the OONI team gathered in Berlin for a
hackfest. Around 20 people ended up showing up and although most of them
were seasoned Oonitarians some fairly new people joined us that I hope
will become part of the growing OONI community.
The scope of the hackfest was that of data analytics and visualization
with special focus on the Tor bridge reachability study we are currently
doing.
# Bridge reachability study
The goal of this study [1] is that of answering some questions
concerning the blocking of Tor bridges [2] and pluggable transport [3]
enabled bridges in the countries of China, Iran, Russia and Ukraine
(test vantage points).
To establish a baseline to eliminate the cases in which the bridge is
marked as blocked, while it is in fact just offline, we measure also
from a vantage point located in the Netherlands.
For every test vantage point we perform two types of measurements:
* A Bridge reachability measurement [4][5] that attempts to build a tor
circuit using the bridge in question
* A TCP connect measurement [6][7] that simply does a TCP connect to the
bridge IP and port
We run both of the measurements to further debug the reason why the
blocking is happening, may this be due to a TCP RST or direct IP
blocking or tor malfunction.
So far this study has been running for a little less than 1 month.
# OONI data pipeline
In order to produce the aggregate data needed to build visualizations we
have built a data pipeline [8]
This consists of a series of operations that are done to the raw reports
in order to strip out sensitive information and place the collected data
into a database.
The nice thing is that the data pipeline we have designed is not
specific to this study, but can and will be in the future expanded to
export data needed to visualize also the other types of measurements
done by OONI.
The data pipeline is comprised of 3 steps (or states, depending on how
you want to look at it).
When the data is submitted to a OONI collector it is synchronized with
the aggregator.
This is a central machine responsible for running all the data
processing tasks, storing the collected data in a database and hosting a
public interface to the sanitised reports. Since all the steps are
independent from one another it is not necessary that they run on the
machine, but it may also be more distributed.
Once the data is on the aggregator machine it is said to be in the RAW
state. The sanitise task is then run on the RAW data to remove sensitive
information and strip out some superfluous information. A RAW copy of
every report is also stored in a private compressed archive for future
reference.
Once the data is sanitised it is said to tbe in SANITISED state. At this
point a import task is run on the data to place it inside of a database.
The SANITISED reports are then place in a directory that is publicly
exposed to the internet to allow people to download also a copy of the
YAML reports.
At this point is is possible to run any export task that performs
queries on the database and produces as output some documents to be used
in the data visualizations (think JSON, CSV, etc.).
# The OONI hackfest
The first day of the hackfest was spent going over the scope of the
project we would be working on in the following days as well as working
in groups that were interested in tacking the design of one aspect of
the problem.
Sticky notes were plentiful and helped us have a clear vision of what
lied ahead of us.
By the end of the first day we had clear what were the set of tasks that
were needed to achieve our goals and which teams would be responsible
for doing what.
The second day was almost entirely dedicated to hacking and everybody
had a task to complete that was either completed by the end of the day
or sooner. Some people even completed their initially assigned task
before the end of the day and came back asking for more!
By the end of the second day we had a real data set to hand over to the
visualization team, to start producing some pretty graphs based on real
data.
We decided that the first visualization we wanted to do should be kept
as simple as possible and be something that we could also use to debug
the data we had collected. It should tell us which bridges were working
when and it should present the information in a way that would highlight
the country involved and the pluggable transport type.
A prototype of it can be seen here:
http://reports.ooni.nu/analytics/bridge_reachability/timeline/
The code for this visualization can be found here:
https://github.com/Shidash/OONI-Bridge-Reachability-Timeline
# Next steps
* Write scripts for generating the bridge_db.json document based on the
data that is given to us from the bridge db team
https://trac.torproject.org/projects/tor/ticket/13570
* Align the dates in the visual timeline
https://trac.torproject.org/projects/tor/ticket/13639
* Better tokenising for bridges so that bridges that have the same
fingerprint, but different transport are grouped properly
https://trac.torproject.org/projects/tor/ticket/13638
* Finish setting up the docker containers for the steps of the data
pipeline
https://trac.torproject.org/projects/tor/ticket/13568
* Setup disaster recovery procedure and backup:
https://trac.torproject.org/projects/tor/ticket/13584
* Setup monitoring of the probes.
https://trac.torproject.org/projects/tor/ticket/12549
* Add support for obfs4
https://trac.torproject.org/projects/tor/ticket/13597
* Set upper bound in comparison with the control in the bridge
reachability timeline
https://trac.torproject.org/projects/tor/ticket/13640
* Make sure that the control measurement is for the specific bridge
measurement
https://trac.torproject.org/projects/tor/ticket/13655
Questions and comments should be directed to the ooni-dev mailing list
or to the #ooni channel on irc.oftc.net.
Have fun!
~ Arturo
[1] https://lists.torproject.org/pipermail/ooni-dev/2014-October/000184.html
[2] https://www.torproject.org/docs/bridges
[3] https://www.torproject.org/docs/pluggable-transports.html.en
[4]
https://gitweb.torproject.org/ooni/spec.git/blob/HEAD:/test-specs/ts-011-br…
[5]
https://gitweb.torproject.org/ooni-probe.git/blob/HEAD:/ooni/nettests/block…
[6]
https://gitweb.torproject.org/ooni/spec.git/blob/HEAD:/test-specs/ts-008-tc…
[7]
https://gitweb.torproject.org/ooni-probe.git/blob/HEAD:/ooni/nettests/block…
[8]
https://github.com/TheTorProject/ooni-pipeline/blob/master/Readme.md#ooni-p…
+tor-dev. tl;dr: Would be nice if there were an HTTP response header
that allows HTTPS servers to indicate their .onion domain names so that
HTTPS Everywhere can automatically redirect to the .onion version in the
future if the user chooses a "use THS when available" preference.
I imagine the header semantics and processing would be similar to HSTS.
It would only be noted when sent over TLS and have the max-age and
include-subdomains fields.
-yan
yan wrote:
> Hi all,
>
> Some people have requested for the "Darkweb Everywhere" extension [1] to
> be integrated into HTTPS Everywhere. This is an extension for Tor
> Browser that redirects users to the Tor Hidden Service version of a
> website when possible.
>
> I'm supportive of the idea; however, I'm worried that since .onion
> domain names are usually unrelated to a site's regular domain name, a
> malicious ruleset would be hard to detect. AFAIK Darkweb Everywhere only
> defends against this by publishing a doc in their Github repo that cites
> evidence for each ruleset [2].
>
> What if, instead, we asked website owners to send an HTTP header that
> indicates the Tor Hidden Service version of their website? Then HTTPS
> Everywhere could cache the result (like HSTS) and redirect to the THS
> version automatically in the future if the user opts-in.
>
> If this is something that EFF/Tor would be willing to advocate for, I
> would be happy to draft a specification for the header syntax and
> intended UA behavior.
>
> Thanks,
> Yan
>
>
> [1] https://github.com/chris-barry/darkweb-everywhere/
> [2]
> https://github.com/chris-barry/darkweb-everywhere/blob/master/doc/EVIDENCE.…
> _______________________________________________
> HTTPS-Everywhere mailing list
> HTTPS-Everywhere(a)lists.eff.org
> https://lists.eff.org/mailman/listinfo/https-everywhere
>
The International Conference on Semantic Web Business and Innovation
(SWBI2015)
The University of Applied Sciences and Arts Western Switzerland (HES-SO
Valais-Wallis)
October 7-9, 2015
http://sdiwc.net/conferences/swbi2015/
All registered papers will be included in SDIWC Digital Library
================================================================
The proposed conference on the above theme will be held at he University
of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)
on October 7-9, 2015 which aims to enable researchers build connections
between different digital applications.
The conference welcomes papers on the following (but not limited to)
research topics:
*Semantic Web and Linked Data
- Database, IR, NLP and AI technologies for the Semantic Web
- Geospatial Semantic Web
- Information Extraction from unstructured data
- Information visualization of Semantic Web data and Linked Data
- Internet of things
- Languages, tools, and methodologies for representing and managing
Semantic Web data
- Linked open data
- Management of Semantic Web data and Linked Data
- Ontology engineering and ontology patterns for the Semantic Web
- Ontology modularity, mapping, merging, and alignment
- Ontology-based data access
- Privacy and Security
- Query and inference over data streams
- Search, query, integration, and analysis on the Semantic Web
- Semantic business process management
- Semantic Sensor networks
- Semantic technologies for mobile platforms
- Semantic Web and Linked Data for Cloud Environments
- Semantic Web, Ontologies
- Social networks and processes on the Semantic Web
- Supporting multi-linguality in the Semantic Web
- User Interfaces and interacting with Semantic Web data and Linked Data
*Business and Innovation in Semantic Web
- Business Model Innovation
- Business Models and E-Commerce
- Business Technology Intelligence
- Challenges for change in semantic services
- Collaborative improvement and innovation
- E-Business Applications and Software
- E-commerce Technology Adoption
- E-commerce, E-Business Strategies
- E-tailing and Multi-Channel selling
- Evolution of Business model for Semantic Web Applications
- High-tech marketing
- Implementation strategies for responsible innovation
- Innovation for E-Business
- Innovative methods and tools for products and services
- Practices and Cases in E-Commerce
- Production of Knowledge Economy
- Technology and Business Transformation
- Technology strategies
- The Latest Trends in Linked Data
- Web Advertising and Web Publishing
- Web and Mobile Applications
Researchers are encouraged to submit their work electronically. All
papers will be fully refereed by a minimum of two specialized referees.
Before final acceptance, all referees comments must be considered.
Important Dates
==============
The Submission is open
Notification of Acceptance: 6 weeks from the submission date
Camera Ready Submission: September 14, 2015
Registration Deadline: September 14, 2015
Conference Dates: October 7-9, 2015
== What is bridge reachability data? ==
By bridge reachability data I'm referring to information about which
Tor bridges are censored in different parts of the world.
The OONI project has been developing a test that allows probes in
censored countries to test which bridges are blocked and which are
not. The test simply takes as input a list of bridges and tests
whether they work. It's also able to test obfuscated bridges with
various pluggable transports (PTs).
== Why do we care about this bridgability data? ==
A few different parties care about the results of the bridge
reachability test [0]. Some examples:
Tor developers and censorship researchers can study the bridge
reachability data to learn which PTs are currently useful around the
world, by seeing which pluggable transports get blocked and where. We
can also learn which bridge distribution mechanisms are busted and
which are not.
Bridge operators, the press, funders and curious people, can learn
which countries conduct censorship and how advanced technology they
use. They can also learn how long it takes jurisdictions to block
public bridges. And in general, they can get a better understanding of
how well Tor is doing in censorship circumvention around the world.
Finally, censored users and world travelers can use the data to learn
which PTs are safe to use in a given jurisdiction.
== Visualizing bridge reachability data ==
So let's look at the data.
Currently, OONI bridge reachability reports look like this:
https://ooni.torproject.org/reports/0.1/CN/bridge_reachability-2014-07-02T0…
and you can retrieve them from this directory listing:
https://ooni.torproject.org/reports/0.1/
That's nice, but I doubt that many people will be able to access (let
alone understand) those reports. Hence, we need some kind of
visualization (and better dir listing) to conveniently display the
data to human beings.
However, a simple x-to-y graph will not suffice: our ploblem is
multidimensional. There are many use cases for the data and bridges
have various characteristics (obfuscation method, distribution method,
etc.) hence there are more than one useful ways to visualize this
dataset.
To give you an idea, I will show you two mockups of visualizations
that I would find useful. Please don't pay attention to the data
itself, I just made some things up while on a train.
Here is one that shows which PTs are blocked in which countries:
https://people.torproject.org/~asn/bridget_vis/countries_pts.jpg The
list would only include countries that are blocking at least a
bridge. Green is "works", red is "blocked". Also, you can imagine the
same visualization, but instead of PT names for columns it has
distribution methods ("BridgeDB HTTP distributor", "BridgeDB mail
distributor", "Private bridge", etc.).
And here is another one that shows how fast jurisdictions block the
default TBB bridges:
https://people.torproject.org/~asn/bridget_vis/tbb_blocked_timeline.jpg
These visualizations could be helpful, but they are not the only ones.
What other use cases do you imagine using this dataset for?
What graphs or visualizations would you like to see?
[0]: Here are some use cases:
Tor developers / Researcers:
*** Which pluggable transports are blocked and where?
*** Do they do DPI? Or did they just block the TBB hardcoded bridges?
*** Which jurisdictions are most aggressive and what blocking technology do they use?
*** Do they block based on IP or on (IP && PORT)?
Users:
*** Which pluggable transport should I use in my jurisdiction?
Bridge operators / Press / Funders / Curious people:
*** Which jurisdictions conduct Tor censorship? (block pluggable transports/distribution methods)
*** How quickly do jurisdictions block bridges?
*** How many users/traffic (and which locations) did the blocked bridges serve?
**** Can be found out through extrainfo descriptors.
*** How well are Tor bridges doing in censorship circumvention?