About 33 bits

Hey, I'm the author of this blog. Much of my previous deanonymization research has been discussed on HN; see <a href="http://www.google.com/search?q=33bits.orgsite:news.ycombinator.com" rel="nofollow">http://www.google.com/search?q=33bits.orgsite:news.ycombinat...</a> Also, if you find the premise of the blog interesting check out the sitemap linked from the page.<p>But since this post is about the About page, let me share a couple of lessons I've learned from the blog, which has been more successful in communicating my research than I'd dared to hope for when I started it 3.5 years ago.<p>1. Those of us working on technical areas often struggle to explain our ideas to others not as technical, in a way that avoids oversimplification and losing essential meaning. Sometimes you'll discover an analogy or metaphor or phrase that does both. Seize those chances, they're powerful.<p>2. Coming up with a name is more important than you might think. If a good name will make your idea or product even 5% stickier, it follows that it may be worthwhile to spend 5% of your time just coming up with the name. One way to do it is to be constantly on the lookout for a good name while you're working on the product.<p>3. If you're writing about something that has policy implications, and want it to be read in Washington, it's hard but not impossible. Two important requirements are to network and build up an audience — they aren't going to read your blog just because it ranks high in Google searches — and to use language that non-technical people can understand.<p>Happy to answer any questions!

I understand the Log2 concept of people able to narrow down something via binary search, but I have a question: don't the "facts" about a person have to divide the remaining population in half (or into smaller chunks)?<p>For instance if you know "Frank" doesn't wear a Rolex, that would not rule out very many people. So statistically, it would probably be better to know if Frank has red hair, as that could rule out a lot more people.<p>Also, let's say you have it narrowed down to four people, but the last bit of information is common to all of them. You now have to get another bit, and possibly another, correct?<p>EDIT: Felt like I didn't express my main point well enough: while you can certainly narrow down people with "bits" of information, information is most of the time not just 1 or 0 and can be fuzzy (or too common) to be useful in a binary search, although with the right bits of information it can of course be fruitful.<p>I'm really interested by this concept and also curious as to if anyone is employing it on a mass scale.

I think the premise is false. You would need about 33 _unique_ bits. I doubt that you can prove the existence of a person-independent algorithm to gather these.

Just out of curoisity, how many bits would it take to include all the people that have ever lived? Also, how many to realistically cover the the future?

On anonymity and privacy... I always thought this was an interesting fact:<p>Birthday, Gender and Zipcode is enough to identify someone uniquely approximately 85% of the time.<p>And a quickly googled source but the meme is older than that: <a href="http://godplaysdice.blogspot.com/2009/12/uniquely-identifying-people-by-birth.html" rel="nofollow">http://godplaysdice.blogspot.com/2009/12/uniquely-identifyin...</a>

&#62; There are only 6.6 billion people in the world, so you only need 33 bits (more precisely, 32.6 bits) of information about a person to determine who they are.<p>I think you should count the dead as well. But then, 33 bits ~= 8 billion, which should still be enough, I guess.