Flimsy Pi Case Still Provides A Level Of Protection

July 5, 2012 by Mike Szczys 14 Comments

This flimsy case isn’t going to protect your Raspberry Pi if you knock it off the workbench. It will provide a level of protection against shorting out from contact with metal objects, or from liquids spilled in the near vicinity. [CGPatterson] ended up making this case from a single sheet of transparency film.

The project is basically papercraft. He started with the dimensions published on the Raspberry Pi FAQ, which turned out to be wrong. Not having a caliper available to help with the precision of the measurements, he grabbed his ruler and did the best he could. The first two cases were a poor fit, but as you can see the third is like a glove. Luckily you don’t have to go through this same trial and error as he release the design. Both A4 and US Letter sized PDFs are available for download. Print them out on the transparency, cut along the lines, apply transparent double-sided tape to the tabs and you’re in business. If you wish to alter the design he has also posted the SVG source he made in Inkscape.

This is certainly a good option for those of us without the ability to produce laser cut parts.

Brute Force A Password Protected PDF Using The BeagleBone

March 26, 2012 by Mike Szczys 19 Comments

The biggest benefit to using the BeagleBone is it’s 700 MHz ARM processor. If you’re just messing around with basic I/O that power is going unused, but [Nuno Alves] is taking advantage of its power. He built a PDF password cracker based on the $85 development board.

We recently saw how easy it is to perform basic I/O using the BeagleBone. Those techniques are in play here, used to drive a character LCD and sample a button input from the breadboard circuit. [Nuno] even published separate posts for each of these peripheral features.

The password protected PDF file is passed to the device on a thumb drive. Since the BeagleBone is running embedded Linux you don’t need to mess around with figuring out how to read from the device. A click of the button starts the process. Currently the code just uses a brute force attack which can test more than 6000 four-character passwords per second. This is quite slow for any password more than four or five characters long, but [Nuno] does mention the possibility of running several ARM processors in parallel, or using a dictionary (or rainbow table) to speed things up. Either way it’s an interesting project to try on the hardware. You can see his video demo of the device after the break.

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LED PDF From TI (KUWTA)

November 21, 2009 by Jakob Griffith 3 Comments

[Satiagraha] let us know that Texas Instruments(TI) has given out a neat “LED Reference Design Cookbook” PDF. The document contains 17 some odd little projects featuring different TI ICs and ways of using them to control LEDs in things from backlights to torches to solar lanterns to advanced PWM control! Sure the document is biased towards using TI equipment, but that shouldn’t stop you from recreating, modifying, and generally just having fun with their designs in your own productions.

Remote Image Processing In JavaScript

March 7, 2009 by Eliot 2 Comments

[youtube=http://www.youtube.com/watch?v=u3_cFel26J8]

[Tom] wrote in to tell us about his JavaScript project for motion detection. It ties together two ideas we’ve talked about recently. The first is doing image processing in-browser using Canvas(), which we’ve seen employed in captcha breaking. The second is offloading heavy processing to browsers, which we saw recently in the MapReduce implementation. [Tom] is using JavaScript to compare consecutive images to determine if there’s any motion. He did this as part of MJPG-Streamer, a program for streaming images from webcams. It can run on very limited hardware, but image processing can be very intensive. Doing the image processing in-browser makes up for this limitation and means that a custom client program doesn’t have to be written. You can find the code here and a PDF about the proof of concept.

PDF Redaction Still Not Working

February 12, 2009 by Eliot 20 Comments

Facebook’s internal valuation was revealed this week thanks to shoddy PDF redaction. Court documents from a settlement between Facebook and ConnectU showed that Facebook values itself at $3.7 billion, much less than the $15 billion that was speculated during the Microsoft investment. The AP uncovered this by cutting and pasting from the redacted court document. It’s the same thing we showed in our PDF redaction screencast last summer… and it will never cease to be funny.

[photo: Bryan Veloso]

Exposing Poorly Redacted PDFs

August 1, 2008 by Eliot 19 Comments

Privacy watchdog group, National Legal and Policy Center has released a PDF detailing Google founder Larry Page’s home (dowload PDF here). They used Google’s Maps and Street View to assemble all of the information. Google is currently involved in a lawsuit resulting from a Street View vehicle traveling and documenting a private road. This PDF was released in response to Google stating that “complete privacy does not exist”.

For some reason the PDF is redacted with black boxes. We threw together a simple screencast (click through for HiDef) to show how to easily bypass the boxes using free tools. You can simply cut and paste the hidden text and images can be copied as well-no need to break out Illustrator. This sort of redaction may seem trivial, but the US military has fallen victim to it in the past.

Lightweight Eye Tracker

January 13, 2006 by Eliot 15 Comments

[Jason S. Babcock] and [Jeff B. Pelz] put together this paper on building a simple, lightweight eyetracker (PDF) to foster the creation of open source eyetracking software. All of the components are mounted to a cheap pair of safety glasses. The eyetracker uses a technique called “dark-pupil” illumination. An IR LED is used to illuminate the eye. The pupil appears as a dark spot because it doesn’t reflect the light. A bright spot also appears on the cornea where the IR is directly reflected. An eye camera is mounted next to the IR LED to record the image of eye with these two spots. Software tracks the difference between the two spots to determine the eye orientation. A laser mounted to the frame helps with the initial calibration process. A scene camera placed above the eye records what the eye is viewing. The video from these two cameras can be compared in real time or after the experiment is concluded.

[thanks austin y.]