Follow your Euro notes in their tracks: "EuroBillTracker is an international non-profit volunteer team dedicated to tracking Euro notes around the world. Each user enters the serial numbers and location information for each note they obtain into EuroBillTracker.

Do ATMs do that too, nowadays?

A posting in joatBlog titled "Ever wonder what happened to Sealand?" made me revisit the cypherpunkish admiration for Sealand followed by much grief. Seem one thing is unchanged: datahavens are an unkept promise.

In the meantime I had the chance to meet one person who claimed he worked for Sealand's once biggest customer and convincingly claimed that:

a) the bandwidth was so unreliable that the whole thing was unusable

b) the location of the server is unproblematic. The real problem is billing. Basically what Mastercard and Visa consider unethically and decide not to process is dead and vice versa. Due to crypto and redundancy servers are a non-issue.
Data can be relocated on demand at least if you only need medium bandwidth.

An interesting thing is that every German law student knows Sealand: When learning what is a state and what isn't a case where the German High Court (?) decided Sealand isn't is widely cited. Also there is a more recent case where somebody claimed he had not pay for a traffic violation because he was a diplomat from Sealand.

We are quite proud to have surpassed all US Universities in the "UCSB Capture The Flag Contest" beeing second after an italian Univeristy.



(To be honest: I think a geostrategic advantage played for us and not superior skills. We could hack from 19:00 to 1:00 because of timezones while in the US they had to hack during the day.)

At the Aachen Summerschool applied IT security Steven J. Murdoch came up with an automatic way to analyze if the thumbnal in a JPEG file is different from the real image. There was widely discussed incident featuring a topless thumbnail and we wanted to know how widespread this problem is. So we crawled the net for images and used Steven's tools to filter for interesting ones. The tool outputs the main image (left) besides the thumbnail (right).

90% of the rest are cropped images. Sometimes just boring stuff has ben cropped, but on other instances interesting details where removed:









Then there are photoshopped images where the Thumbnail reveals the base for the modification:






Then there are a lot of Images where the Background has been removed:




Probably this is the most scary image: There the face has been obscured but the thumbnail contained the original face:



And finally there seem to be images where there are no similarities between the main image and the thumbnail:



And with certain images the tool sees differences where no differences are visible to the human eye: