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• Data Privacy Day 2020

  27 janvier 2020, par Matthieu Aubry — Privacy
  It’s January 28th which means it’s Data Privacy Day !

  Today is an important day for the Matomo team as we reflect on our mission and our goals for 2020. This year I wanted to send a video message to all Matomo users, community members and customers. 

  Check it out (full transcript below)

  

  A video message from Matomo founder, Matthieu Aubry

  Privacy-friendly alternatives

  • NoMoreGoogle :
    a comprehensive list giving you options for other privacy-friendly alternatives.
  • Switching.Software :
    Ethical alternatives to popular sites and apps.
  • Web browser :
    Firefox
    Brave
    Vivaldi
  • Search engine :
    DuckDuckGo
    Qwant
  • File sharing :
    Nextcloud
  • Email provider :
    ProtonMail
    Mailfence
    Tutanota

  Video transcript

  Hey everyone,

  Matthieu here, Founder of Matomo.

  Today is one of the most significant days of the year for the Matomo team – it’s Data Privacy Day. And so I wanted to quickly reflect on our mission and the significance of this day. 

  In today’s busy online world where data is king, this day is an important reminder of being vigilant in protecting our personal information online.

  Matomo began 12 years ago as an open-source alternative to Google Analytics – the goal was, and still is to give full control of data back to users. 

  In 2020, we are determined to see through this commitment. We will keep building a powerful and ethical web analytics platform that focuses on privacy protection, data ownership, and provides value to all Matomo users and customers.

  And what’s fantastic is to see the rise of other quality software companies offering privacy-friendly alternatives for web browsers, search engines, file sharing, email providers, all with a similar mission. And with these products now widely available, we encourage you to take back control of all your online activities and begin this new decade with a resolution to stay safe online.

  I’ll provide you with some links below the video to check out these privacy-friendly alternatives. If you have a website and want to gain valuable insights on the visitors while owning your data, join us ! 

  Matomo Analytics On-Premise is and always will be free to download and install on your own servers and on your own terms.

  Also feel free to join our active community or spread the word to your friends and network about the importance of data privacy.

  Thank you all and wishing you a great 2020 !

  For more information on how Matomo protects the privacy of your users, visit : https://matomo.org/privacy/

  Do you have privacy concerns ?

  What better day than today to speak up ! What privacy concerns have you experienced ?

  Contact Support

• FFMPEG Audio/video out of sync after cutting and concatonating even after transcoding

  4 mai 2020, par Ham789

  I am attempting to take cuts from a set of videos and concatonate them together with the concat demuxer.

  



  However, the audio is out of sync of the video in the output. The audio seems to drift further out of sync as the video progresses. Interestingly, if I click to seek another time in the video with the progress bar on the player, the audio becomes synced up with the video but then gradually drifts out of sync again. Seeking to a new time in the player seems to reset the audio/video. It is like they are being played back at different rates or something. I get this behaviour in both Quicktime and VLC players.

  



  For each video, I decode it, trim a clip from it and then encode it to 4k resolution at 25 fps with its audio :

  



  ffmpeg -ss 0.5 -t 0.5 -i input_video1.mp4 -r 25 -vf scale=3840:2160 output_video1.mp4

  



  I then take each of these videos and concatonate them together with the concat demuxer :

  



  ffmpeg -f concat -safe 0 -i cut_videos.txt -c copy -y output.mp4

  



  I am taking short cuts of each video (approximately 0.5s)

  



  I am using Python's subprocess to automate the cutting and concatonating of the videos.

  



  I am not sure if this happens because of the trimming or concatenation steps but when I play back the intermediate cut video files (output_video1.mp4 in the above command), there seems to be some silence before the audio comes in at the start of the video.

  



  When I concatonate the videos, I sometimes get a lot of these warnings however the audio still becomes out of sync even when I do not get them :

  



  [mp4 @ 0000021a252ce080] Non-monotonous DTS in output stream 0:1; previous: 51792, current: 50009; changing to 51793. This may result in incorrect timestamps in the output file.

  



  From this post, it seems to be a problem with cutting the videos and their timestamps. The solution proposed in the post is to decode, cut and then encode the video however I am already doing that.

  



  How can I ensure the audio and video are in sync ? Am I transcoding incorrectly ? This seems to be the only solution I can find online however it does not seem to work.

  



  UPDATE :

  



  I took inspiration from this post and seperated the audio and video from output_video1.mp4 using :

  



  ffmpeg -i output_video1.mp4 -acodec copy -vn video.mp4

  



  and

  



  ffmpeg -i output_video1.mp4 -vcodec copy -an audio.mp4

  



  I then compared the durations of video.mp4 and audio.mp4 and got 0.57s and 0.52s respectively. Since the video is longer, this explains why there is a period of silence in the videos. The post then suggests transcoding is the solution however as you can see from the code above that does not work for me.

  



  Sample Output Log for the Trim Command

  



    built with Apple LLVM version 10.0.0 (clang-1000.11.45.5)
  configuration: --prefix=/usr/local/Cellar/ffmpeg/4.2.2 --enable-shared --enable-pthreads --enable-version3 --enable-avresample --cc=clang --host-cflags='-I/Library/Java/JavaVirtualMachines/adoptopenjdk-13.0.1.jdk/Contents/Home/include -I/Library/Java/JavaVirtualMachines/adoptopenjdk-13.0.1.jdk/Contents/Home/include/darwin' --host-ldflags= --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libbluray --enable-libmp3lame --enable-libopus --enable-librubberband --enable-libsnappy --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libx264 --enable-libx265 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-librtmp --enable-libspeex --enable-libsoxr --enable-videotoolbox --disable-libjack --disable-indev=jack
  libavutil      56. 31.100 / 56. 31.100
  libavcodec     58. 54.100 / 58. 54.100
  libavformat    58. 29.100 / 58. 29.100
  libavdevice    58.  8.100 / 58.  8.100
  libavfilter     7. 57.100 /  7. 57.100
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  5.100 /  5.  5.100
  libswresample   3.  5.100 /  3.  5.100
  libpostproc    55.  5.100 / 55.  5.100
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'input_video1.mp4':
  Metadata:
    major_brand     : isom
    minor_version   : 512
    compatible_brands: isomiso2avc1mp41
    encoder         : Lavf58.29.100
  Duration: 00:00:04.06, start: 0.000000, bitrate: 14266 kb/s
    Stream #0:0(und): Video: h264 (High) (avc1 / 0x31637661), yuv420p, 3840x2160, 14268 kb/s, 30 fps, 30 tbr, 15360 tbn, 60 tbc (default)
    Metadata:
      handler_name    : Core Media Video
    Stream #0:1(und): Audio: aac (LC) (mp4a / 0x6134706D), 44100 Hz, mono, fltp, 94 kb/s (default)
    Metadata:
      handler_name    : Core Media Audio
File 'output_video1.mp4' already exists. Overwrite ? [y/N] y
Stream mapping:
  Stream #0:0 -> #0:0 (h264 (native) -> h264 (libx264))
  Stream #0:1 -> #0:1 (aac (native) -> aac (native))
Press [q] to stop, [?] for help
[libx264 @ 0x7fcae4001e00] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2
[libx264 @ 0x7fcae4001e00] profile High, level 5.1
[libx264 @ 0x7fcae4001e00] 264 - core 155 r2917 0a84d98 - H.264/MPEG-4 AVC codec - Copyleft 2003-2018 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=12 lookahead_threads=2 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
Output #0, mp4, to 'output_video1.mp4':
  Metadata:
    major_brand     : isom
    minor_version   : 512
    compatible_brands: isomiso2avc1mp41
    encoder         : Lavf58.29.100
    Stream #0:0(und): Video: h264 (libx264) (avc1 / 0x31637661), yuv420p, 3840x2160, q=-1--1, 25 fps, 12800 tbn, 25 tbc (default)
    Metadata:
      handler_name    : Core Media Video
      encoder         : Lavc58.54.100 libx264
    Side data:
      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
    Stream #0:1(und): Audio: aac (LC) (mp4a / 0x6134706D), 44100 Hz, mono, fltp, 69 kb/s (default)
    Metadata:
      handler_name    : Core Media Audio
      encoder         : Lavc58.54.100 aac
frame=   14 fps=7.0 q=-1.0 Lsize=     928kB time=00:00:00.51 bitrate=14884.2kbits/s dup=0 drop=1 speed=0.255x    
video:922kB audio:5kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.194501%
[libx264 @ 0x7fcae4001e00] frame I:1     Avg QP:21.06  size:228519
[libx264 @ 0x7fcae4001e00] frame P:4     Avg QP:22.03  size: 85228
[libx264 @ 0x7fcae4001e00] frame B:9     Avg QP:22.88  size: 41537
[libx264 @ 0x7fcae4001e00] consecutive B-frames: 14.3%  0.0%  0.0% 85.7%
[libx264 @ 0x7fcae4001e00] mb I  I16..4: 27.6% 64.3%  8.1%
[libx264 @ 0x7fcae4001e00] mb P  I16..4:  9.1% 10.7%  0.2%  P16..4: 48.5%  7.3%  3.9%  0.0%  0.0%    skip:20.2%
[libx264 @ 0x7fcae4001e00] mb B  I16..4:  1.1%  1.0%  0.0%  B16..8: 44.5%  2.9%  0.2%  direct: 8.3%  skip:42.0%  L0:45.6% L1:53.2% BI: 1.2%
[libx264 @ 0x7fcae4001e00] 8x8 transform intra:58.2% inter:93.4%
[libx264 @ 0x7fcae4001e00] coded y,uvDC,uvAC intra: 31.4% 62.2% 5.2% inter: 11.4% 30.9% 0.0%
[libx264 @ 0x7fcae4001e00] i16 v,h,dc,p: 15% 52% 12% 21%
[libx264 @ 0x7fcae4001e00] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 19% 33% 32%  2%  2%  2%  4%  2%  4%
[libx264 @ 0x7fcae4001e00] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 20% 39%  9%  3%  4%  4% 12%  3%  4%
[libx264 @ 0x7fcae4001e00] i8c dc,h,v,p: 43% 36% 18%  3%
[libx264 @ 0x7fcae4001e00] Weighted P-Frames: Y:0.0% UV:0.0%
[libx264 @ 0x7fcae4001e00] ref P L0: 69.3%  8.0% 14.8%  7.9%
[libx264 @ 0x7fcae4001e00] ref B L0: 88.1%  9.2%  2.6%
[libx264 @ 0x7fcae4001e00] ref B L1: 90.2%  9.8%
[libx264 @ 0x7fcae4001e00] kb/s:13475.29
[aac @ 0x7fcae4012400] Qavg: 125.000```


  


• 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.