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• What is data anonymization in web analytics ?

  11 février 2020, par Joselyn Khor — Analytics Tips, Privacy
  Collecting information via web analytics platforms is needed to help a website grow and improve. When doing so, it’s best to strike a balance between getting valuable insights, and keeping the trust of your users by protecting their privacy.

  This means not collecting or processing any personally identifiable information (PII). But what if your organisation requires you to collect PII ?

  That’s where data anonymization comes in.

  

  What is data anonymization ?

  Data anonymization makes identifiable information unidentifiable. This is done through data processing techniques which remove or modify PII data. So data becomes anonymous and can’t be linked to any individual.

  In the context of web analytics, data anonymization is handy because you can collect useful data while protecting the privacy of website visitors.

  Why is data anonymization important ?

  Through modern threats of identity theft, credit card fraud and the like, data anonymization is a way to protect the identity and privacy of individuals. As well as protect private and sensitive information of organisations. 

  Data anonymization lets you follow the many laws around the world which protect user privacy. These laws provide safeguards around collecting personal data or personally identifiable information (PII), so data anonymization is a good solution to ensure you’re not processing such sensitive information.

  In some cases, implementing data anonymization techniques means you can avoid having to show your users a consent screen. Which means you may not need to ask for consent in order to track data. This is a bonus as consent screens can annoy and stop people from engaging with your site.

  GDPR and data anonymization

  

  The GDPR is a law in the EU that limits the collection and processing of personal data. The aim is to give people more control over their online personal information. Which is why website owners need to follow certain rules to become GDPR compliant and protect user privacy. According to the GDPR, you can be fined up to 4% of your yearly revenue for data breaches or non-compliance. 

  In the case of web analytics, tools can be easily made compliant by following a number of steps. 

  This is why anonymizing data is a big deal.

  Anonymized data isn’t personal data according to the GDPR : 

  “The principles of data protection should therefore not apply to anonymous information, namely information which does not relate to an identified or identifiable natural person or to personal data rendered anonymous in such a manner that the data subject is not or no longer identifiable.”

  This means, you still get the best of both worlds. By anonymizing data, you’re still able to collect useful information like visitor behavioural data.

  US privacy laws and data anonymization

  In the US, there isn’t one single law that governs the protection of personal data, called personally identifiable information (PII). There are hundreds of federal and state laws that protect the personal data of US residents. As well as, industry-specific statutes related to data privacy, like the California Consumer Privacy Act (CCPA) and the Health Insurance Portability and Accountability Act (HIPAA).

  Website owners in the US need to know exactly what laws govern their area of business in order to follow them.

  A general guideline is to protect user privacy regardless of whether you are or aren’t allowed to collect PII. This means anonymizing identifiable information so your website users aren’t put at risk.

  Data anonymization techniques in Matomo Analytics

  If you carry these out, you won’t need to ask your website visitors for tracking consent since anonymized data is no longer considered personal data under the GDPR.

  • Anonymize previously tracked raw data – like visitors/visits
  • Anonymize Visitor IP addresses
  • Anonymize geo-location information (country, region, city)
  • Pseudonymize User ID ( if you don’t want this data to land on your Matomo server, the solution is simply to not set the User ID. Then Matomo will use the normal anonymized IDs)
  • Data can also be anonymized before it’s even sent to Matomo
  • Learn how to further configure privacy settings in a web analytics tool like Matomo
  • 11 ways Matomo Analytics helps you to protect your visitors privacy

  The techniques listed above make it easy for you when using a tool like Matomo, as they are automatically anonymized.

  Tools like Google Analytics on the other hand don’t provide some of the privacy options and leave it up to you to take on the burden of implementation without providing steps.

  Data anonymization tools

  If you’re a website owner who wants to grow your business or learn more about your website visitors, privacy-friendly tools like Matomo Analytics are a great option. By following the easy steps to be GDPR compliant, you can anonymize all data that could put your visitors at risk.

• How to correctly setup Linker in Eclipse IDE 4.8.0M4 for ffmpeg development (Ubuntu)

  28 janvier 2018, par boergi

  I am using Eclipse IDE 4.8.0M4 on Ubunto 16.04. I try to compile the code from a FFmpeg tutorial on GitHUB : (https://github.com/leandromoreira/ffmpeg-libav-tutorial/blob/master/0_hello_world.c). For setting up FFmpeg in Eclipse i used this guide :(https://trac.ffmpeg.org/wiki/Setup_Eclipse_IDE_for_FFmpeg_(Linux)).

  The header files and libaries are all in the folder /home/git/ffmpeg. (e.g. avcodec.h and libavcodec.a is in the folder /home/git/ffmpeg/libavcodec). Included libs : -lavcodec -lpostproc -lz -llzma -lrt -lavfilter -lswresample -lavdevice -lswscale -lavutil -lavformat

  Console output :

  12:34:30 **** Incremental Build of configuration Debug for project ffmpeg_test ****
  
  make all 
  
  Building target: ffmpeg_test
  
  Invoking: GCC C Linker
  
  gcc -L/home/git/ffmpeg/libavcodec -L/home/git/ffmpeg/libavformat -o "ffmpeg_test"  ./src/simpletest.o   -lavcodec -lpostproc -lz -llzma -lrt -lavfilter -lswresample -lavdevice -lswscale -lavutil -lavformat
  
  ./src/simpletest.o: In function `main':
  
  /home/boergi/eclipse-workspace/ffmpeg_test/Debug/../src/simpletest.c:141: undefined reference to `avcodec_parameters_to_context'
  
  /home/boergi/eclipse-workspace/ffmpeg_test/Debug/../src/simpletest.c:163: undefined reference to `av_packet_alloc'
  
  /home/boergi/eclipse-workspace/ffmpeg_test/Debug/../src/simpletest.c:194: undefined reference to `av_packet_free'
  
  ./src/simpletest.o: In function `decode_packet':
  
  /home/boergi/eclipse-workspace/ffmpeg_test/Debug/../src/simpletest.c:214: undefined reference to `avcodec_send_packet'
  
  /home/boergi/eclipse-workspace/ffmpeg_test/Debug/../src/simpletest.c:225: undefined reference to `avcodec_receive_frame'
  
  collect2: error: ld returned 1 exit status
  
  makefile:30: recipe for target 'ffmpeg_test' failed
  
  make: *** [ffmpeg_test] Error 1
  
  
  
  12:34:31 Build Finished (took 519ms)

  I found out that "int avcodec_parameters_to_context(AVCodecContext *codec, const AVCodecParameters *par)" is defined in utils.c (also in the /libavcodec folder), but i don’t know what can i do to get this running.

  boergi@Ubuntu-b:~/git/ffmpeg$ ffmpeg -version
  
  ffmpeg version N-89895-g7723750 Copyright (c) 2000-2018 the FFmpeg developers
  
  built with gcc 5.4.0 (Ubuntu 5.4.0-6ubuntu1~16.04.5) 20160609
  
  configuration: 
  
  libavutil      56.  7.100 / 56.  7.100
  
  libavcodec     58.  9.100 / 58.  9.100
  
  libavformat    58.  5.101 / 58.  5.101
  
  libavdevice    58.  0.101 / 58.  0.101
  
  libavfilter     7. 11.101 /  7. 11.101
  
  libswscale      5.  0.101 /  5.  0.101
  
  libswresample   3.  0.101 /  3.  0.101

• It’s January 28th : Let’s celebrate Data Privacy !

  29 janvier 2018, par Matomo Core Team

  It is a special Sunday here for us at Matomo, as today is international Data Privacy Day. The day was created in 2007 to raise awareness of the importance of data privacy for people and businesses worldwide.

  

  What is data privacy about ?

  Personal data refers to any data which is collected and can be linked to an individual human being such as phone records, credit card transactions, GPS position, IP addresses, browsing history… So basically, personal data refers to your identity online. That is why you should be highly concerned about sending your personal data (or your customers’ personal data) away. It is important to be aware of who is collecting the information and how it is being used.

  What big changes are happening in 2018 ?

  New privacy regulations GDPR comes into play next May 2018 : GDPR will bring about some changes (in the right direction) by making people and businesses aware of what data privacy means, and what they should be doing to protect their customers’ privacy. With these new regulations, data privacy awareness is reaching a critical milestone this year.

  How can I protect my privacy ?

  Here are a few tips to protect your privacy :

  • Educate yourself on the importance of privacy : the more informed you are the better.
  • Use open source solutions where you can keep full control of your own data (such as NextCloud instead of Dropbox and of course Matomo instead of Google Analytics),
  • Experiment with different online services to protect your data privacy, for example using an alternative search engine (such as DuckDuckGo instead of Google) or an alternative email provider (such as ProtonMail).

  What’s coming next for Matomo and Privacy ?

  Here at Matomo, we are building the leading decentralised open web analytics platform. We’re currently working on new sets of privacy features to make compliance with GDPR a breeze. Stay tuned here to be notified when we launch the new privacy compliance tools !

  And in case you’ve missed this important info, you may be interested in :

  • Configure Privacy Settings in Matomo
  • 11 ways Matomo Analytics helps you to protect your visitors privacy

   

  The post It’s January 28th : Let’s celebrate Data Privacy ! appeared first on Analytics Platform - Matomo.