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Monthly archive (2016-02)

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On the impact of machine learning (on privacy)

| | 2016.02.23. 05:02:01  Gulyás Gábor  

I've recently read an article where the author pictured a future where Google-glass-like products can support our decisions by using face recognition and similar techniques. While the author definitely aimed to picture a 'new bright future', she remained silent about potential abuses and privacy issues. Plus, while the technology has a definite direction toward as she desribed, this still leaves the writing as a piece of science fiction at the moment. But where exactly we are now, and for how long we may be reliefed?

Today, using machine learning (ML) is a hard task. First, you need to get vast amounts of quality data, then picking the proper algorithm, training and using it is also highly non-trivial. Not to mention hardware requirements, as the training requires a lot of computation power, and it takes a while until your application learns understanding the task it is designed to do. This might sound comforting from a privacy-focused aspect, but that would be inadequate to do so.

I see three major issues that could result a change in the state of the art, and I think – for some of these – we are already in the shifting phase:

  1. Machine learning based applications should fit an average smartphone. Last year, we could see a nice pioneering example of real-time (pretrained) machine learning with Google translate: it could detect text from the camera in real time (text recognition), it could translate the given text (with deep neural networks), then it could replace the original text with its translation. This kind of applications should fit in low-end phones, too. This is likely to hapen in one, or two years.
  2. Currently programs are trained remotely due to resources issues. Training phase needs to be shifted to the consumer side, to be done on smart phones. In a couple of years we might have specialized chips in smartphones that enable this, opening up the way of new types of applications.
  3. Developing applications that use machine learning should be easier. There are a lot of research andeducational activities around machine learning nowadays, but we can't stay that machine learning could be a simple import-and-use tool in general in the future. For some specific tasks, data types it might be, but that's all what we can see now.

It is easy to imagine that such ML could provide an exponential amount of privacy-infringing uses (*). However, we should not forget that today the data driven businesses fuel machine learning research and application development. Thus, there are already thousands of services that are built around data and machine learning. As many of these companies use data that was not gathered by user consent (just to mention at least one possible privacy violation), ML is already here to erode further our privacy.

Let's have some examples. BlueCava, a company that uses fingerprinting to track people on the web, is using machine learning to connect devices that belong to the same person. This is just an example; with little effort we could find a miriad of other companies who analyse user behavior, buying intent, fields of interests, etc. with similar techniques. Data that we generate is also at stake: we could think about smartphones and wareable devices, but also the posts we write.

To conclude shortly, machine learning already has a huge impact that should increase incredibly in the next few years. All big companies have their own research groups in the field, and if we are honest to ourselves, we know this is for a simple reason: use machine learning in their products in order to increase their revenues.


(*) I intentionally did not want to add a comment to if machines could became alive. I think here you can read a realistic opinion on the topic.


This post originally appeared in the professional blog of Gábor Gulyás.

Tags: google, privacy, web privacy, google glass, data privacy, machine learning


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MyTrackingChoices: An attempt to end the AdBlock war

| | 2016.02.11. 05:18:33  Jagdish Achara  
In the last few years, as a result of the proliferation of intrusive and privacy-invading ads, the use of ad-blockers and anti-tracking tools have become widespread. As of the second quarter of this year, 16% of online Americans, about 45 million people, had installed ad-blocking software, according to PageFair 2015 report. Meanwhile, 77 millions Europeans are blocking ads. All this accounts globally for $21,8 billion worth of blocked ads. The Internet economy is in danger since ads fuel the free content and services over Internet.

As opposed to existing ad blockers that take a binary approach (i.e., block everything if you install them or block nothing otherwise), MyTrackingChoices aims to provide users fine-grained choices about tracking and thereby, categories of Web pages where they're ok or not to receive ads. MyTrackingChoices allows users to choose on which sites (more specifically, on which categories of sites) they want to block the trackers. For example, a user can choose to block the trackers and therefore, ads, on sites related to health or religion, but may choose not to block the trackers on sites related to sports or news.

We assume that a significant proportion of users are not against advertisements, but want to keep control over their data. We believe that some sites are more sensitive than others. In fact, most people don’t want to be tracked on “sensitive” websites (for example related to religion, health,…), but don’t see any problem to be tracked on less sensitive ones (such as news, sport,…). This extension allows you to take control and specify which on which categories of sites you don’t want to be tracked on! Furthermore, the extension also gives you the option to block the trackers on specific websites.

This solution is different from other anti-tracking tools in two ways. First, existing anti-tracking tools give users the option to decide by which entity they don't want to be tracked. However, we believe that most users are concerned with other dimension, i.e., where they don't want to be tracked. Also, this is easy for most users to understand and configure the categories of the websites that are sensitive to them instead of choosing what trackers they want to block. Therefore, we provide this option to users. Secondly, unlike other anti-tracking or ad-blocking tools, we don't block the network requests of all trackers right away because this has an effect on Internet economy. We let user choose the categories (health, religion) of Web-pages that are privacy-sensitive to them and block the trackers on those pages only. 

Tags: web bug, transparency-enhancing technologies, web tracking


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