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• What Is Data Misuse & How to Prevent It ? (With Examples)

  13 mai 2024, par Erin

  Your data is everywhere. Every time you sign up for an email list, log in to Facebook or download a free app onto your smartphone, your data is being taken.

  This can scare customers and users who fear their data will be misused.

  While data can be a powerful asset for your business, it’s important you manage it well, or you could be in over your head.

  In this guide, we break down what data misuse is, what the different types are, some examples of major data misuse and how you can prevent it so you can grow your brand sustainably.

  What is data misuse ?

  Data is a good thing.

  It helps analysts and marketers understand their customers better so they can serve them relevant information, products and services to improve their lives.

  But it can quickly become a bad thing for both the customers and business owners when it’s mishandled and misused.

  

  Data misuse is when a business uses data outside of the agreed-upon terms. When companies collect data, they need to legally communicate how that data is being used. 

  Who or what determines when data is being misused ?

  Several bodies :

  • User agreements
  • Data privacy laws
  • Corporate policies
  • Industry regulations

  There are certain laws and regulations around how you can collect and use data. Failure to comply with these guidelines and rules can result in several consequences, including legal action.

  Keep reading to discover the different types of data misuse and how to prevent it.

  3 types of data misuse

  There are a few different types of data misuse.

  If you fail to understand them, you could face penalties, legal trouble and a poor brand reputation.

  

  1. Commingling

  When you collect data, you need to ensure you’re using it for the right purpose. Commingling is when an organisation collects data from a specific audience for a specific reason but then uses the data for another purpose.

  One example of commingling is if a company shares sensitive customer data with another company. In many cases, sister companies will share data even if the terms of the data collection didn’t include that clause.

  Another example is if someone collects data for academic purposes like research but then uses the data later on for marketing purposes to drive business growth in a for-profit company.

  In either case, the company went wrong by not being clear on what the data would be used for. You must communicate with your audience exactly how the data will be used.

  2. Personal benefit

  The second common way data is misused in the workplace is through “personal benefit.” This is when someone with access to data abuses it for their own gain.

  The most common example of personal benefit data muse is when an employee misuses internal data.

  While this may sound like each instance of data misuse is caused by malicious intent, that’s not always the case. Data misuse can still exist even if an employee didn’t have any harmful intent behind their actions. 

  One of the most common examples is when an employee mistakenly moves data from a company device to personal devices for easier access.

  3. Ambiguity

  As mentioned above, when discussing commingling, a company must only use data how they say they will use it when they collect it.

  A company can misuse data when they’re unclear on how the data is used. Ambiguity is when a company fails to disclose how user data is being collected and used.

  This means communicating poorly on how the data will be used can be wrong and lead to misuse.

  One of the most common ways this happens is when a company doesn’t know how to use the data, so they can’t give a specific reason. However, this is still considered misuse, as companies need to disclose exactly how they will use the data they collect from their customers.

  Laws on data misuse you need to follow

  Data misuse can lead to poor reputations and penalties from big tech companies. For example, if you step outside social media platforms’ guidelines, you could be suspended, banned or shadowbanned.

  But what’s even more important is certain types of data misuse could mean you’re breaking laws worldwide. Here are some laws on data misuse you need to follow to avoid legal trouble :

  General Data Protection Regulation (GDPR)

  The GDPR, or General Data Protection Regulation, is a law within the European Union (EU) that went into effect in 2018.

  The GDPR was implemented to set a standard and improve data protection in Europe. It was also established to increase accountability and transparency for data breaches within businesses and organisations.

  The purpose of the GDPR is to protect residents within the European Union.

  The penalties for breaking GDPR laws are fines up to 20 million Euros or 4% of global revenues (whatever the higher amount is).

  The GDPR doesn’t just affect companies in Europe. You can break the GDPR’s laws regardless of where your organisation is located worldwide. As long as your company collects, processes or uses the personal data of any EU resident, you’re subject to the GDPR’s rules.

  If you want to track user data to grow your business, you need to ensure you’re following international data laws. Tools like Matomo—the world’s leading privacy-friendly web analytics solution—can help you achieve GDPR compliance and maintain it.

  With Matomo, you can confidently enhance your website’s performance, knowing that you’re adhering to data protection laws. 

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

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  California Consumer Privacy Act (CCPA)

  The California Consumer Privacy Act (CCPA) is another important data law companies worldwide must follow.

  Like GDPR, the CCPA is a data privacy law established to protect residents of a certain region — in this case, residents of California in the United States.

  The CCPA was implemented in 2020, and businesses worldwide can be penalised for breaking the regulations. For example, if you’re found violating the CCPA, you could be fined $7,500 for each intentional violation.

  If you have unintentional violations, you could still be fined, but at a lesser fee of $2,500.

  The Gramm-Leach-Bliley Act (GLBA)

  If your business is located within the United States, then you’re subject to a federal law implemented in 1999 called The Gramm-Leach-Bliley Act (GLB Act or GLBA).

  The GLBA is also known as the Financial Modernization Act of 1999. Its purpose is to control the way American financial institutions handle consumer data. 

  In the GLBA, there are three sections :

  1. The Financial Privacy Rule : regulates the collection and disclosure of private financial data.
  2. Safeguards Rule : Financial institutions must establish security programs to protect financial data.
  3. Pretexting Provisions : Prohibits accessing private data using false pretences.

  The GLBA also requires financial institutions in the U.S. to give their customers written privacy policy communications that explain their data-sharing practices.

  4 examples of data misuse in real life

  If you want to see what data misuse looks like in real life, look no further.

  Big tech is central to some of the biggest data misuses and scandals.

  

  Here are a few examples of data misuse in real life you should take note of to avoid a similar scenario :

  1. Facebook election interference

  One of history’s most famous examples of data misuse is the Facebook and Cambridge Analytica scandal in 2018.

  During the 2018 U.S. midterm elections, Cambridge Analytica, a political consulting firm, acquired personal data from Facebook users that was said to have been collected for academic research.

  Instead, Cambridge Analytica used data from roughly 87 million Facebook users. 

  This is a prime example of commingling.

  The result ? Cambridge Analytica was left bankrupt and dissolved, and Facebook was fined $5 billion by the Federal Trade Commission (FTC).

  2. Uber “God View” tracking

  Another big tech company, Uber, was caught misusing data a decade ago. 

  Why ?

  Uber implemented a new feature for its employees in 2014 called “God View.”

  The tool enabled Uber employees to track riders using their app. The problem was that they were watching them without the users’ permission. “God View” lets Uber spy on their riders to see their movements and locations.

  The FTC ended up slapping them with a major lawsuit, and as part of their settlement agreement, Uber agreed to have an outside firm audit their privacy practices between 2014 and 2034.

  

  3. Twitter targeted ads overstep

  In 2019, Twitter was found guilty of allowing advertisers to access its users’ personal data to improve advertisement targeting.

  Advertisers were given access to user email addresses and phone numbers without explicit permission from the users. The result was that Twitter ad buyers could use this contact information to cross-reference with Twitter’s data to serve ads to them.

  Twitter stated that the data leak was an internal error. 

  4. Google location tracking

  In 2020, Google was found guilty of not explicitly disclosing how it’s using its users’ personal data, which is an example of ambiguity.

  The result ?

  The French data protection authority fined Google $57 million.

  8 ways to prevent data misuse in your company

  Now that you know the dangers of data misuse and its associated penalties, it’s time to understand how you can prevent it in your company.

  

  Here are eight ways you can prevent data misuse :

  1. Track data with an ethical web analytics solution

  You can’t get by in today’s business world without tracking data. The question is whether you’re tracking it safely or not.

  If you want to ensure you aren’t getting into legal trouble with data misuse, then you need to use an ethical web analytics solution like Matomo.

  With it, you can track and improve your website performance while remaining GDPR-compliant and respecting user privacy. Unlike other web analytics solutions that monetise your data and auction it off to advertisers, with Matomo, you own your data.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  2. Don’t share data with big tech

  As the data misuse examples above show, big tech companies often violate data privacy laws.

  And while most of these companies, like Google, appear to be convenient, they’re often inconvenient (and much worse), especially regarding data leaks, privacy breaches and the sale of your data to advertisers.

  Have you ever heard the phrase : “You are the product ?” When it comes to big tech, chances are if you’re getting it for free, you (and your data) are the products they’re selling.

  The best way to stop sharing data with big tech is to stop using platforms like Google. For more ideas on different Google product alternatives, check out this list of Google alternatives.

  3. Identity verification 

  Data misuse typically isn’t a company-wide ploy. Often, it’s the lack of security structure and systems within your company. 

  An important place to start is to ensure proper identity verification for anyone with access to your data.

  4. Access management

  After establishing identity verification, you should ensure you have proper access management set up. For example, you should only give specific access to specific roles in your company to prevent data misuse.

  5. Activity logs and monitoring

  One way to track data misuse or breaches is by setting up activity logs to ensure you can see who is accessing certain types of data and when they’re accessing it.

  You should ensure you have a team dedicated to continuously monitoring these logs to catch anything quickly.

  6. Behaviour alerts 

  While manually monitoring data is important, it’s also good to set up automatic alerts if there is unusual activity around your data centres. You should set up behaviour alerts and notifications in case threats or compromising events occur.

  7. Onboarding, training, education

  One way to ensure quality data management is to keep your employees up to speed on data security. You should ensure data security is a part of your employee onboarding. Also, you should have regular training and education to keep people informed on protecting company and customer data.

  8. Create data protocols and processes 

  To ensure long-term data security, you should establish data protocols and processes. 

  To protect your user data, set up rules and systems within your organisation that people can reference and follow continuously to prevent data misuse.

  Leverage data ethically with Matomo

  Data is everything in business.

  But it’s not something to be taken lightly. Mishandling user data can break customer trust, lead to penalties from organisations and even create legal trouble and massive fines.

  You should only use privacy-first tools to ensure you’re handling data responsibly.

  Matomo is a privacy-friendly web analytics tool that collects, stores and tracks data across your website without breaking privacy laws.

  With over 1 million websites using Matomo, you can track and improve website performance with :

  • Accurate data (no data sampling)
  • Privacy-friendly and compliant with privacy regulations like GDPR, CCPA and more
  • Advanced features like heatmaps, session recordings, A/B testing and more

  Try Matomo free for 21-days. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

  Your email address
  

  Your website address
  

  Your Analytics subdomain will be .matomo.cloud (change)

  Choose your analytics subdomain
  

  .matomo.cloud

  I accept the terms and conditions and data processing agreement (DPA)

  
  Your information will be used to create an account on our cloud service. For more information please consult our privacy policy.
  
  
  

  Start improving your websites now

  

• Data Privacy Issues to Be Aware of and How to Overcome Them

  9 mai 2024, par Erin

  Data privacy issues are a significant concern for users globally.

  Around 76% of US consumers report that they would not buy from a company they do not trust with their data. In the European Union, a 2021 study found that around 53% of EU internet users refused to let companies access their data for advertising purposes.

  These findings send a clear message : if companies want to build consumer trust, they must honour users’ data privacy concerns. The best way to do this is by adopting transparent, ethical data collection practices — which also supports the simultaneous goal of maintaining compliance with regional data privacy acts.

  So what exactly is data privacy ?

  

  Data privacy refers to the protections that govern how personal data is collected and used, especially with respect to an individual’s control over when, where and what information they share with others.

  Data privacy also refers to the extent to which organisations and governments go to protect the personal data that they collect. Different parts of the world have different data privacy acts. These regulations outline the measures organisations must take to safeguard the data they collect from their consumers and residents. They also outline the rights of data subjects, such as the right to opt out of a data collection strategy and correct false data. 

  As more organisations rely on personal data to provide services, people have become increasingly concerned about data privacy, particularly the level of control they have over their data and what organisations and governments do with their data.

  Why should organisations take data privacy issues seriously ?

  Organisations should take data privacy seriously because consumer trust depends on it and because they have a legal obligation to do so. Doing so also helps organisations prevent threat actors from illegally accessing consumer data. Strong data privacy helps you : 

  Comply with data protection acts

  Organisations that fail to comply with regional data protection acts could face severe penalties. For example, consider the General Data Protection Regulation (GDPR), which is the primary data protection action for the European Union. The penalty system for GDPR fines consists of two tiers :

  • Less severe infringements — Which can lead to fines of up to €10 million (or 2% of an organisation’s worldwide annual revenue from the last financial year) per infringement.
  • More severe infringements — This can lead to fines of up to €20 million (or 4% of an organisation’s worldwide annual revenue from the last financial year) per infringement.

  The monetary value of these penalties is significant, so it is in the best interest of all organisations to be GDPR compliant. Other data protection acts have similar penalty systems to the GDPR. In Brazil, organisations non-compliant with the Lei Geral de Proteção de Dados Pessoais (LGPD) could be fined up to 50 million reals (USD 10 million) or 2% of their worldwide annual revenue from the last financial year.

  Improve brand reputation

  Research shows that 81% of consumers feel that how an organisation treats their data reflects how they treat them as a consumer. This means a strong correlation exists between how people perceive an organisation’s data collection practices and their other business activities.

  

  Data breaches can have a significant impact on an organisation, especially their reputation and level of consumer trust. In 2022, hackers stole customer data from the Australian private health insurance company, Medibank, and released the data onto the dark web. Optus was also affected by a cyberattack, which compromised the information of current and former customers. Following these events, a study by Nature revealed that 83 percent of Australians were concerned about the security of their data, particularly in the hands of their service providers.

  Protect consumer data

  Protecting consumer data is essential to preventing data breaches. Unfortunately, cybersecurity attacks are becoming increasingly sophisticated. In 2023 alone, organisations like T-Mobile and Sony have been compromised and their data stolen.

  One way to protect consumer data is to retain 100% data ownership. This means that no external parties can see your data. You can achieve this with the web analytics platform, Matomo. With Matomo, you can store your own data on-premises (your own servers) or in the Cloud. Under both arrangements, you retain full ownership of your data.

  Try Matomo for Free

  Get the web insights you need, while respecting user privacy.

  Start for free

  No credit card required

  What are the most pressing data privacy issues that organisations are facing today ?

  Today’s most pressing data privacy challenges organisations face are complying with new data protection acts, maintaining consumer trust, and choosing the right web analytics platform. Here is a detailed breakdown of what these challenges mean for businesses.

  Complying with new and emerging data protection laws

  Ever since the European Union introduced the GDPR in 2018, other regions have enacted similar data protection acts. In the United States, California (CCPA), Virginia (VCDPA) and Colorado have their own state-level data protection acts. Meanwhile, Brazil and China have the General Data Protection Law (LGPD) and the Personal Information Protection Law (PIPL), respectively.

  For global organisations, complying with multiple data protection acts can be tough, as each act interprets the GDPR model differently. They each have their own provisions, terminology (or different interpretations of the same terminology), and penalties.

  A web analytics platform like Matomo can help your organisation comply with the GDPR and similar data protection acts. It has a range of privacy-friendly features including data anonymisation, IP anonymisation, and first-party cookies by default. You can also create and publish custom opt-out forms and let visitors view your collected data.

  

  Today’s most pressing data privacy challenges organisations face are complying with new data protection acts, maintaining consumer trust, and choosing the right web analytics platform. Here is a detailed breakdown of what these challenges mean for businesses.

  Complying with new and emerging data protection laws

  Ever since the European Union introduced the GDPR in 2018, other regions have enacted similar data protection acts. In the United States, California (CCPA), Virginia (VCDPA) and Colorado have their own state-level data protection acts. Meanwhile, Brazil and China have the General Data Protection Law (LGPD) and the Personal Information Protection Law (PIPL), respectively.

  For global organisations, complying with multiple data protection acts can be tough, as each act interprets the GDPR model differently. They each have their own provisions, terminology (or different interpretations of the same terminology), and penalties.

  A web analytics platform like Matomo can help your organisation comply with the GDPR and similar data protection acts. It has a range of privacy-friendly features including data anonymisation, IP anonymisation, and first-party cookies by default. You can also create and publish custom opt-out forms and let visitors view your collected data.

  Try Matomo for Free

  Get the web insights you need, while respecting user privacy.

  Start for free

  No credit card required

  Maintaining consumer trust

  Building (and maintaining) consumer trust is a major hurdle for organisations. Stories about data breaches and data scandals — notably the Cambridge Analytical scandal — instil fear into the public’s hearts. After a while, people wonder, “Which company is next ?”

  One way to build and maintain trust is to be transparent about your data collection practices. Be open and honest about what data you collect (and why), where you store the data (and for how long), how you protect the data and whether you share data with third parties. 

  You should also prepare and publish your cyber incident response plan. Outline the steps you will take to contain, assess and manage a data breach.

  Choosing the right web analytics platform

  Organisations use web analytics to track and monitor web traffic, manage advertising campaigns and identify potential revenue streams. The most widely used web analytics platform is Google Analytics ; however, many users have raised concerns about privacy issues. 

  When searching for a Google Analytics alternative, consider a web analytics platform that takes data privacy seriously. Features like cookieless tracking, data anonymisation and IP anonymisation will let you track user activity without collecting personal data. Custom opt-out forms will let your web visitors enforce their data subject rights.

  What data protection acts exist right now ?

  

  As time goes on and more countries introduce their own data privacy laws, it becomes harder for organisations to adapt. Understanding the basics of each act can help streamline compliance. Here is what you need to know about the latest data protection acts.

  General Data Protection Regulation (GDPR)

  The GDPR is a data protection act created by the European Parliament and Council of the European Union. It comprises 11 chapters covering the general provisions, principles, data subject rights, penalties and other relevant information.

  The GDPR established a framework for organisations and governments to follow regarding the collection, processing, storing, transferring and deletion of personal data. Since coming into effect on 25 May 2018, other countries have used the GDPR as a model to enact similar data protection acts.

  General Data Protection Law (LGPD)

  The LGPD is Brazil’s main data protection act. The Federal Republic of Brazil signed the act on August 14, 2018, and it officially commenced on August 16, 2020. The act aimed to unify the 40 Brazilian laws that previously governed the country’s approach to processing personal data.

  Like the GDPR, the LGPD serves as a legal framework to regulate the collection and usage of personal data. It also outlines the duties of the national data protection authority, the Autoridade Nacional de Proteção de Dados (ANPD), which is responsible for enforcing the LGPD.

  Privacy Amendment (Notifiable Data Breaches) for the Privacy Act 1988

  Established by the Australian House of Representatives, the Privacy Act 1988 outlines how organisations and governments must manage personal data. The federal government has amended the Privacy Act 1988 twice — once in 2000, and again in 2014 — and is committing to a significant overhaul.

  The new proposals will make it easier for individuals to opt out of data collection, organisations will have to destroy collected data after a reasonable period, and small businesses will no longer be exempt from the Privacy Act.

  United States

  

  The United States does not have a federally mandated data protection act. Instead, each state has been gradually introducing its data protection acts, with the first being California, followed by Virginia and Colorado. Over a dozen other states are following suit, too.

  • California — The then-Governor of California Jerry Brown signed the California Consumer Privacy Act (CCPA) into law on June 28, 2018. The act applies to organisations with gross annual revenue of more than USD 25 million, and that buy or sell products and services to 100,000 or more households or consumers.
  • Virginia — The Virginia Consumer Data Protection Act (VCDPA) took effect on January 1, 2023. It applies to organisations that process (or control) the personal data of 100,000 or more consumers in a financial year. It also applies to organisations that process (or control) the personal data of 25,000 or more consumers and gain more than 50% of gross revenue by selling that data.
  • Colorado — Colorado Governor Jared Polis signed the Colorado Privacy Act (ColoPA) into law in July 2021. The act applies to organisations that process (or control) the personal data of 100,000 or more Colorado residents annually. It also applies to organisations that earn revenue from the sale of personal data of at least 25,000 Colorado residents.

  Because the US regulations are a patchwork of differing legal acts, compliance can be a complicated endeavour for organisations operating across multiple jurisdictions. 

  How can organisations comply with data protection acts ?

  One way to ensure compliance is to keep up with the latest data protection acts. But that is a very time-consuming task.

  Over 16 US states are in the process of signing new acts. And countries like China, Turkey and Australia are about to overhaul — in a big way — their own data privacy protection acts. 

  Knowledge is power. But you also have a business to run, right ? 

  That’s where Matomo comes in.

  Streamline data privacy compliance with Matomo

  Although data privacy is a major concern for individuals and companies operating in multiple parts of the world — as they must comply with new, conflicting data protection laws — it is possible to overcome the biggest data privacy issues.

  Matomo enables your visitors to take back control of their data. You can choose where you store your data on-premises and in the Cloud (EU-based). You can use various features, retain 100% data ownership, protect visitor privacy and ensure compliance.

  Try the 21-day free trial of Matomo today, start your free analytics trial. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

  Your email address
  

  Your website address
  

  Your Analytics subdomain will be .matomo.cloud (change)

  Choose your analytics subdomain
  

  .matomo.cloud

  I accept the terms and conditions and data processing agreement (DPA)

  
  Your information will be used to create an account on our cloud service. For more information please consult our privacy policy.
  
  
  

  Start improving your websites now

  

• FFmpeg player backporting to Android 2.1 - one more problem

  22 avril 2024, par tretdm

  I looked for a lot of information about how to build and use FFmpeg in early versions of Android, looked at the source codes of players from 2011-2014 and was able to easily build FFmpeg 4.0.4 and 3.1.4 on the NDKv5 platform. I have highlighted the main things for this purpose :

  


  

  • <android></android>bitmap.h> and <android></android>native_window.h> before Android 2.2 (API Level 8) such a thing did not exist

  


  • this requires some effort to implement buffer management for A/V streams, since in practice, when playing video, the application silently crashed after a few seconds due to overflow (below code example in C++ and Java)

  


  • FFmpeg - imho, the only way to support a sufficient number of codecs that are not officially included in Android 2.1 and above

  


  


  void decodeVideoFromPacket(JNIEnv *env, jobject instance,
                           jclass mplayer_class, AVPacket avpkt, 
                           int total_frames, int length) {
    AVFrame     *pFrame = NULL
    AVFrame     *pFrameRGB = NULL;
    pFrame = avcodec_alloc_frame();
    pFrameRGB = avcodec_alloc_frame();
    int frame_size = avpicture_get_size(PIX_FMT_RGB32, gVideoCodecCtx->width, gVideoCodecCtx->height);
    unsigned char* buffer = (unsigned char*)av_malloc((size_t)frame_size * 3);
    if (!buffer) {
        av_free(pFrame);
        av_free(pFrameRGB);
        return;
    }
    jbyteArray buffer2;
    jmethodID renderVideoFrames = env->GetMethodID(mplayer_class, "renderVideoFrames", "([BI)V");
    int frameDecoded;
    avpicture_fill((AVPicture*) pFrame,
                   buffer,
                   gVideoCodecCtx->pix_fmt,
                   gVideoCodecCtx->width,
                   gVideoCodecCtx->height
                  );

    if (avpkt.stream_index == gVideoStreamIndex) { // If video stream found
        int size = avpkt.size;
        total_frames++;
        struct SwsContext *img_convert_ctx = NULL;
        avcodec_decode_video2(gVideoCodecCtx, pFrame, &frameDecoded, &avpkt);
        if (!frameDecoded || pFrame == NULL) {
            return;
        }

        try {
            PixelFormat pxf;
            // RGB565 by default for Android Canvas in pre-Gingerbread devices.
            if(android::get_android_api_version(env) >= ANDROID_API_CODENAME_GINGERBREAD) {
                pxf = PIX_FMT_BGR32;
            } else {
                pxf = PIX_FMT_RGB565;
            }

            int rgbBytes = avpicture_get_size(pxf, gVideoCodecCtx->width,
                                            gVideoCodecCtx->height);

            // Converting YUV to RGB frame & RGB frame to char* buffer 
            
            buffer = convertYuv2Rgb(pxf, pFrame, rgbBytes); // result of av_image_copy_to_buffer()

            if(buffer == NULL) {
                return;
            }

            buffer2 = env->NewByteArray((jsize) rgbBytes);
            env->SetByteArrayRegion(buffer2, 0, (jsize) rgbBytes,
                                    (jbyte *) buffer);
            env->CallVoidMethod(instance, renderVideoFrames, buffer2, rgbBytes);
            env->DeleteLocalRef(buffer2);
            free(buffer);
        } catch (...) {
            if (debug_mode) {
                LOGE(10, "[ERROR] Render video frames failed");
                return;
            }
        }
    }
}


  


  private void renderVideoFrames(final byte[] buffer, final int length) {
        new Thread(new Runnable() {
            @Override
            public void run() {
                Canvas c;
                VideoTrack track = null;
                for (int tracks_index = 0; tracks_index < tracks.size(); tracks_index++) {
                    if (tracks.get(tracks_index) instanceof VideoTrack) {
                        track = (VideoTrack) tracks.get(tracks_index);
                    }
                }
                if (track != null) {
                    int frame_width = track.frame_size[0];
                    int frame_height = track.frame_size[1];
                    if (frame_width > 0 && frame_height > 0) {
                        try {
                            // RGB_565  == 65K colours (16 bit)
                            // RGB_8888 == 16.7M colours (24 bit w/ alpha ch.)
                            int bpp = Build.VERSION.SDK_INT > 9 ? 16 : 24;
                            Bitmap.Config bmp_config =
                                    bpp == 24 ? Bitmap.Config.RGB_565 : Bitmap.Config.ARGB_8888;
                            Paint paint = new Paint();
                            if(buffer != null && holder != null) {
                                holder.setType(SurfaceHolder.SURFACE_TYPE_NORMAL);
                                if((c = holder.lockCanvas()) == null) {
                                    Log.d(MPLAY_TAG, "Lock canvas failed");
                                    return;
                                }
                                ByteBuffer bbuf =
                                        ByteBuffer.allocateDirect(minVideoBufferSize);
                                bbuf.rewind();
                                for(int i = 0; i < buffer.length; i++) {
                                    bbuf.put(i, buffer[i]);
                                }
                                bbuf.rewind();

                                // The approximate location where the application crashed.
                                Bitmap bmp = Bitmap.createBitmap(frame_width, frame_height, bmp_config);
                                bmp.copyPixelsFromBuffer(bbuf);
                                
                                float aspect_ratio = (float) frame_width / (float) frame_height;
                                int scaled_width = (int)(aspect_ratio * (c.getHeight()));
                                c.drawBitmap(bmp,
                                        null,
                                        new RectF(
                                                ((c.getWidth() - scaled_width) / 2), 0,
                                                ((c.getWidth() - scaled_width) / 2) + scaled_width,
                                                c.getHeight()),
                                        null);
                                holder.unlockCanvasAndPost(c);
                                bmp.recycle();
                                bbuf.clear();
                            } else {
                                Log.d(MPLAY_TAG, "Video frame buffer is null");
                            }
                        } catch (Exception ex) {
                            ex.printStackTrace();
                        } catch (OutOfMemoryError oom) {
                            oom.printStackTrace();
                            stop();
                        }
                    }
                }
            }
        }).start();
    }


  


  Exception (tested in Android 4.1.2 emulator) :

  


  E/dalvikvm-heap: Out of memory on a 1228812-byte allocation
I/dalvikvm: "Thread-495" prio=5 tid=21 RUNNABLE
   ................................................
     at android.graphics.Bitmap.nativeCreate(Native Method)
     at android.graphics.Bitmap.createBitmap(Bitmap.java:640)
     at android.graphics.Bitmap.createBitmap(Bitmap.java:620)
     at [app_package_name].MediaPlayer$5.run(MediaPlayer.java:406)
     at java.lang.Thread.run(Thread.java:856)


  


  For clarification : I first compiled FFmpeg 0.11.x on a virtual machine with Ubuntu 12.04 LTS from my written build script, looked for player examples suitable for Android below 2.2 (there is little information about them, unfortunately) and opened the file on the player and after showing the first frames it crashed into a stack or buffer overflow, on I put off developing the player for some time.

  


  Is there anything ready-made that, as a rule, fits into one C++ file and takes into account all the nuances of backporting ? Thanks in advance.