Presentations and papers on the project topics

Here are some presentation and papers on the project topics (GSM, A5, etc.).

•  GSM: Radio interface, basic introduction to GSM.
•  About the GSM-Dm-Channels, very nice paper about GSM, suitable for beginners.

•  The A5 Cracking Project - Practical attacks on GSM using GNU Radio and FPGAs, presentation at Chaos Communication Camp 2007 by Steve, Joshua Lackey and David Hulton ( video).
  Note: see the first question from the public and especially the answer.

•  Intercepting Mobile Phone/GSM Traffic, presentation at BlackHat? Europe 08 by David Hulton and Steve ( video).

•  A Real-World Attack Breaking A5/1 within Hours - article by Timo Gendrullis, Martin Novotny and Andy Ruppiz about cracking A5 using  COPACOBANA (special hardware built by  FPGA's.

•  Anatomy of smartphone hardware - Dissecting contemporary cellphone hardware, presentation at 25th Chaos Communication Congress by Harald Welte ( PDF presentation).

•  Locating Mobile Phones using SS7 presentation at 25th Chaos Communication Congress by Tobias Engel ( PDF presentation).

•  Running your own GSM network presentation at 25th Chaos Communication Congress by Dieter Spaar and Harald Welte ( PDF presentation).

•  Collection of papers about cracking A5 in 1998 and 1999 by jya.com.

•  A Hardware-Based Attack on the A5/1 Stream Cipher, paper by Jorg Keller and Birgit Seitz, 2001.

•  Making a Faster Cryptanalytic Time-Memory Trade-Off, paper by Philippe Oechslin, 2003

•  Les compromis temps-mémoire et leur utilisation pour casser les mots de passe Windows, paper (in French) by Philippe Oechslin, 2004

•  Cryptanalytic Time/Memory/Data Tradeoffs for Stream Ciphers, paper by Alex Biryukov and Adi Shamir, 1976.

•  Mars: A MapReduce Framework on Graphics Processors, paper by Bingsheng He Wenbin, Fang Naga K. Govindaraju and Qiong Luo Tuyong Wang, 2007. MapReduce? is a distributed programming framework originally proposed by Google for the ease of development of web search applications on a large number of CPUs. Mars hides the programming complexity of

the GPU behind the simple and familiar MapReduce? interface and is up to 16 times faster than its CPU-based counterpart for six common web applications on a quad-core machine.