Recherche avancée

Sur d’autres sites (8495)

• What is PII ? Your introduction to personally identifiable information

  15 janvier 2020, par Joselyn Khor — Analytics Tips, Privacy, Security
  Most websites you visit collect information about you via tools like Google Analytics and Matomo – sometimes collecting personally identifiable information (PII).

  When it comes to PII, people are becoming more concerned about data privacy. Identifiable information can be used for illegal purposes like identity theft and fraud. 

  So how can you protect yourself as an innocent internet browser ? In the case of website owners – how do you protect users and your company from falling prey to privacy breaches ?

  

  As one of the most trusted analytics companies, we feel our readers would benefit from being as informed as possible about data privacy issues and PII. Learn what it means, and what you can do to keep yours or others’ information safe.

  Table of Contents

  What does PII stand for ?

  PII acronym

  PII is an acronym for personally identifiable information.

  PII definition

  Personally identifiable information (PII) is a term used predominantly in the United States.

  The appendix of OMB M-10-23 (Guidance for Agency Use of Third-Party Website and Applications) gives this definition for PII :

  “The term ‘personally identifiable information’ refers to information which can be used to distinguish or trace an individual’s identity, such as their name, social security number, biometric records, etc. alone, or when combined with other personal or identifying information which is linked or linkable to a specific individual, such as date and place of birth, mother’s maiden name, etc.”

  What can be considered personally identifiable information (PII) ? Some PII examples :

  • Full name/usernames
  • Home address/mailing address
  • Email address
  • Credit card numbers
  • Date of birth
  • Phone numbers
  • Login details

  • Precise locations
  • Account numbers
  • Passwords
  • Security codes (including biometric records)
  • Personal identification numbers
  • Driver license number
  • Get a more comprehensive list here

  What’s non-PII ?

  Anonymous information, or information that can’t be traced back to an individual, can be considered non-PII.

  Who is affected by the exploitation of PII ?

  Anyone can be affected by the exploitation of personal data, where you have identity theft, account fraud and account takeovers. When websites resort to illegally selling or sharing your data and compromising your privacy, the fear is falling victim to such fraudulent activity. 

  PII can also be an issue when employees have access to the database and the data is not encrypted. For example, anyone working in a bank can access your accounts ; anyone working at Facebook may be able to read your messages. This shows how privacy breaches can easily happen when employees have access to PII.

  Website owner’s responsibility for data privacy (PII and analytics)

  To respect your website visitor’s privacy, best practice is to avoid collecting PII whenever possible. If you work in an industry which requires people to disclose personal information (e.g. healthcare, security industries, public sector), then you must ensure this data is collected and handled securely. 

  

  The US National Institute of Standards and Technology states : “The likelihood of harm caused by a breach involving PII is greatly reduced if an organisation minimises the amount of PII it uses, collects, and stores. For example, an organisation should only request PII in a new form if the PII is absolutely necessary.” 

  How you’re held accountable remains up to the privacy laws of the country you’re doing business in. Make sure you are fully aware of the privacy and data protection laws that relate specifically to you. 

  To reduce the risk of privacy breaches, try collecting as little PII as you can ; purging it as soon as you can ; and making sure your IT security is updated and protected against security threats. 

  If you’re using data collection tools like web analytics, data may be tracked through features like User ID, custom variables, and custom dimensions. Sometimes they are also harder to identify when they are present, for example, in page URLs, page titles, or referrers URLs. So make sure you’re optimising your web analytics tools’ settings to ensure you’re asking your users for consent and respecting users’ privacy.

  If you’re using a GDPR compliant tool like Matomo, learn how you can stop processing such personal data

  PII, GDPR and businesses in the US/EU

  Because PII is broad, you may run into confusion when considering PII and GDPR (which applies in the EU). The General Data Protection Regulation (GDPR) provides more safeguards for user privacy.

  GDPR grants people in the EU more rights concerning their “personal data” (more on PII vs personal data below). In the EU the GDPR restricts the collection and processing of personal data. The repercussions are severe penalties and fines for privacy infringements. Businesses are required to handle this personal data carefully. You can be fined up to 4% of their yearly revenue for data breaches or non-compliance. 

  

  Although there isn’t an overarching data protection law in the US, there are hundreds of laws on both the federal and state levels to protect the personal data of US residents. US Congress has also enacted industry-specific statutes related to data privacy, and the state of California passed the California Consumer Privacy Act. 

  To be on the safe side, if you are using analytics, follow matters relating to “personal data” in the GDPR. It’s all-encompassing when it comes to protecting user privacy. GDPR rules still apply whenever an EU citizen visits any non EU site (that processes personal data).

  Personally identifiable information (PII) vs personal data

  PII and “personal data” aren’t used interchangeably. All personal data can be PII, but not all PII can be defined as personal data.

  The definition of “personal data” according to the GDPR :

  

  This means “personal data” encompasses a greater number of identifiers which include the online sphere. Examples include : IP addresses and URL names. As well as seemingly “innocent” data like height, job position, company etc. 

  What’s considered personal data depends on the context. If a piece of information can be combined with others to establish someone’s identity then that can be considered personal data. 

  Under GDPR, when processing personal data, you need explicit consent. You need to ensure you’re compliant according to GDPR definitions of “personal data” not just what’s considered “PII”.

  How Matomo deals with PII and personal data

  Although Matomo Analytics is a web analytics software that tracks user activity on your website, we take privacy and PII very seriously – on both our Cloud and On-Premise offerings. 

  If you’re using Matomo and would like to know how you can be fully GDPR compliant and protect user privacy, read more :
  

  • Learn how to not process any personally identifiable information – Anonymise IP addresses, user IDs, and order IDs
  • Matomo protects user privacy by talking the talk and walking the walk
  • Stay ahead of the GDPR with a privacy-respecting analytics platform
  • 11 ways Matomo helps you protect your visitor’s privacy

  Disclaimer

  We are not lawyers and don’t claim to be. The information provided here is to help give an introduction to issues you may encounter when dealing with PII. We encourage every business and website to take data privacy seriously and discuss these issues with your lawyer if you have any concerns. 

  Additional resources :

  • https://www.consumeraffairs.com/finance/identity-theft-statistics.html#identity-theft-trends-in-2019
  • https://ec.europa.eu/info/law/law-topic/data-protection_en
  • https://iclg.com/practice-areas/data-protection-laws-and-regulations/usa
  • https://www.csoonline.com/article/3215864/how-to-protect-personally-identifiable-information-pii-under-gdpr.html
  • https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/key-definitions/what-is-personal-data/

• Failed to decode HLS by FFMpeg command. Invalid NAL unit 0

  9 mars 2024, par Fyodor Khruschov

  On front-end I create stream with chrome.tabCapture.capture or navigator.mediaDevices.getDisplayMedia methods. Then send chunks generated by MediaRecorder to server. On the server I have FFMpeg command which decodes chunks into .mp4 file. This is the command :

  


  ffmpeg -y -i - -preset veryfast -tune zerolatency -filter_complex [0:v]split=3[v1][v2][v3];[v1]scale=w=-2:h=1080,fps=30[v1out];[v2]scale=w=-2:h=720,fps=30[v2out];[v3]scale=w=-2:h=480,fps=30[v3out] -map [v1out] -maxrate:0 6M -bufsize:0 12M -keyint_min 100 -g 100 -map [v2out] -maxrate:1 3M -bufsize:1 6M -keyint_min 100 -g 100 -map [v3out] -maxrate:2 1.5M -bufsize:2 3M -keyint_min 100 -g 100 -c:v libx264 -map a:0 -c:a:0 aac -b:a:0 128k -ac 2 -map a:0 -c:a:1 aac -b:a:1 96k -map a:0 -c:a:2 aac -b:a:2 96k -f hls -hls_time 2 -hls_playlist_type vod -hls_flags independent_segments+temp_file -hls_segment_type fmp4 -hls_segment_filename ./output/ready/output_%v_%03d.m4s -var_stream_map v:0,a:0 v:1,a:1 v:2,a:2 -master_pl_name master.m3u8 ./output/ready/stream_%v.m3u8 -map 0:v:0 -map 0:a:0 -c:v copy -c:a aac ./output/download/video.mp4 -map 0:a:0 -ar 16000 -ac 1 -c:a pcm_s16le ./output/captions/audio.wav -loglevel info


  


  During the process of decoding I have these errors in logs :

  


  [extract_extradata @ 0x60000264b250] Invalid NAL unit 0, skipping.
[h264 @ 0x13ff04e60] Invalid NAL unit 0, skipping.
[h264 @ 0x13ff04e60] co located POCs unavailable
[h264 @ 0x13ff04e60] negative number of zero coeffs at 17 0
[h264 @ 0x13ff04e60] error while decoding MB 17 0
[h264 @ 0x13ff04e60] concealing 3388 DC, 3388 AC, 3388 MV errors in B frame
[h264 @ 0x13ff04e60] missing picture in access unit with size 24158
[h264 @ 0x13ff04e60] Invalid NAL unit 0, skipping.
[h264 @ 0x13ff04e60] data partitioning is not implemented. Update your FFmpeg version to the newest one from Git. If the problem still occurs, it means that your file has a feature which has not been implemented.
[h264 @ 0x13ff04e60] If you want to help, upload a sample of this file to https://streams.videolan.org/upload/ and contact the ffmpeg-devel mailing list. (ffmpeg-devel@ffmpeg.org)
[h264 @ 0x13ff04e60] no frame!
[h264 @ 0x13ff04e60] Unknown SAR index: 18.
[h264 @ 0x13ff04e60] Invalid NAL unit 0, skipping.
[h264 @ 0x13ff04e60] Unknown SAR index: 18.
[h264 @ 0x13ff04e60] number of reference frames (2+4) exceeds max (5; probably corrupt input), discarding one
[h264 @ 0x13ff04e60] number of reference frames (3+3) exceeds max (5; probably corrupt input), discarding one
[h264 @ 0x13ff04e60] number of reference frames (4+2) exceeds max (5; probably corrupt input), discarding one
[h264 @ 0x13ff04e60] FMO is not implemented. Update your FFmpeg version to the newest one from Git. If the problem still occurs, it means that your file has a feature which has not been implemented.
[h264 @ 0x13ff04e60] sps_id 4 out of range


  


  This issue is very inconsistent and happen in rare cases (I can't understand the logic). Most of the time chunks decoded successfully, but sometimes not.

  


  How to understand where the issue is coming from ? Is it possible for FFMpeg to skip wrong data and generate mp4 file anyway even with glitches, but don't crush ?

  


• How to save audio chunks from client to ffmpeg readable file ?

  22 septembre 2023, par LuckOverflow

  I am live recording audio data from a TS React front-end and need to send it to the server, where it can be saved to a file so that ffmpeg can mix it. The front-end saves the mic data to a blob with type "mimeType : "audio/webm ; codecs=opus" when printed in the browser terminal. I send the exact object that I printed to the server, where logging it indicates it is a, or was passed as a, "Buffer" object.

  


  I have tried saving that Buffer as a webm file, but when I pass that file as an input to ffmpeg ffprobe, I get the error "Format matroska,webm detected only with a low score of 1..." and "EBML header parsing failed.." "Invalid data found when processing input." I have tried several other formats to no success.

  


  I need a way to transform this Buffer object to an audio file that can be mixed by ffmpeg. When I am finished, I also need to be able to do the reverse operation to send it in the same format to another client for playback, which is currently working.

  


  Code that records and sends the audio (TS React) :

  


  React Record

  


  const startRecording = async function () {
    inputStream = await navigator.mediaDevices.getUserMedia({ audio: true });
   
    mediaRecorder.current = new MediaRecorder(inputStream, { mimeType: "audio/webm; codecs=opus" });

    mediaRecorder.current.ondataavailable = e => {
      console.log(e.data)
      if (e.data.size > 0) {
        socket.emit("recording", e.data);
        console.log("Audio data recorded. Transmitting to server via socketio...");
      }
    };

    mediaRecorder.current.start(1000);
  };



  


  Code that receives and tries to save the Buffer to a file (JS Node.js) :

  


  Server Receive

  


  socket.on("recording", (chunk) => {
    console_log("Audio chunk recieved. Transmitting to frontend...");
    socket.broadcast.emit('listening', chunk);

    fs.writeFileSync('out.webm', chunk.toString());
    if (counter > 3) {
      console.log("Trying ffmpeg...");

      ffmpegInstance
        .input('out.webm')
        .complexFilter([
          {
            filter: 'amix'
          }])
        .save('./Music/FFMPEGSTREAM.mp3');
    }

    counter++;
  });


  


  fluent-ffmpeg interface package is includued in the server code, but I have been using ffmpeg in the terminal (Pop OS) to debug. The goal is to save the file to a ram disk and use fluent ffmpeg to mix before sending to a different client for playback. Currently I am just trying to save it to disk and get ffmpeg command line to work on it.

  


  Update :
Problem was that the chunk I was analyzing didn't have the header info. MediaRecorder encodes, then slices it up, not slices it up into your specified time slot and encodes. I have not found a good solution to this. Saving the file, without toString I believe, results in a playable webm when the header is properly included.