It's been a whirlwind few weeks at the labs: First off, we have received plenty of media coverage regarding ICanStalkU lately: New Scientist, ABCNews.com, CNET, Forbes.com, and the BBC.
Next, ICanStalkU was presented at The Next HOPE.You can download the slides here:
- Locational Privacy and Wholesale Surveillance via Photo Services (PPT, 7.8MB)
- Locational Privacy and Wholesale Surveillance via Photo Services (PDF, 5.1MB)
The tools we released are available on Google Code.
One thing that you may notice in the presentation is that we talk about releasing a dataset of URLs of geo-tagged photos. This brings us to a slight change in our plans. After talking to people after the presentation, we've reconsidered releasing the dataset.
First off, while we still are committed that the idea behind ICanStalkU is a good one and public outreach is important, we were asked what purpose does the dataset serve and we couldn't come up with a good answer. It is a very interesting collection of information, but does it serve any purpose beyond publicly exposing user's locations? We're not sure. Also after some discussion, we think that releasing this information may change the conversation from "People are posting this information online so that anyone can get it!" to "Hackers are recording your location!", which, while technically true, gets away from the fact that anyone can do this and it hardly takes a degree in rocket science to do so. If a couple of security geeks, some open source tools, and a dirt cheap virtual server can amass a sizable dataset in a few months on a shoestring budget, imagine what could be possible if someone, say a corporation or a government decided to toss some money and time at similar project?
Also, as we are part of the "If you don't need it, why log it?" camp, we are also going to start regularly purging our database of any content older then 6 hours, so that if something happens and the data does get out into the open, the amount of people exposed will be fairly limited.
In summary, we think that the dataset crosses a line without having a tangible benefit. We apologize if you were looking forward to analyze it.