Fingerprinting Computers – Part I – Your browser.

Authentication is about the only big open problem in the practice of internet security. The existing encryption and hashing algorithms as well as the key generation/management protocols offer a high degree of security, barring programming/implementation errors.
Authentication technologies face serious challenges mainly because identity is difficult to establish with a 100% certainty even using physical characteristics, i.e., signatures and credentials can be forged, the physical appearance of people can be manipulated, etc.
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Check the strength of passwords

A cool application for checking the strength of passwords

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More reviews for the AMS

I have a few new reviews of papers on cryptography in my updated page. For those interested in the security of NMAC and HMAC or affiliation hiding key exchanges, I recommend reading the reviews. They include links to relevant papers.

Power-up of a SRAM as a source of Entropy and Identification

Many years ago I was involved in a research project looking to use tiny differences in processing time inside a computer as a way to fingerprint the device. The idea was not unique, I guess that at the same time many were busy looking for similar things.

The reason was that in the framework of Internet security protocols such as SSL, if each party can fingerprint the other party’s computer, that will add another dimension to the development of a strong authentication scheme. Eventually the company supporting the research run out of interest and money and I forgot all about the idea until I recently read the news.

Enter the Fingerprint Extraction and Random Numers in SRAM (FERNS) method developed by Holcomb,  Burleson and Fu of the University of California Berkeley. They analyzed the initial state of the cells of a 512 kb Static Random Access Memory (SRAM) after power up and discovered that the stable states of some cells representing the bits were random, that is they have equal probability to be 1 or 0, while others cells were skewed to start as a 1 or as a 0. This property of the cells is due to imperfections of the fabrication process and are impossible to control.

A paper describing Burleson’s group work is going to appears in the IEEE Transactions on Computers.

From the Abstract
…..  We use experimental data from high performance SRAM, and the WISP UHF RFID tag to validate the principles behind FERNS. We demonstrate that 8 byte fingerprints from an SRAM chip are sufficient for uniquely identifying circuits among a population of 5,120 and extrapolate that 16 to 24 bytes of SRAM would be sufficient for uniquely identifying every instance of the SRAM ever produced. Using a smaller population, we demonstrate similar identifying ability from the embedded SRAM microcontroller memory of the WISP. In addition to identification, we show that SRAM fingerprints capture noise, enabling true random number generation. We demonstrate that the initial states of a 256 byte SRAM can produce 128 bit true random numbers capable of passing the NIST approximate entropy test.

The possibilities for the application of this technology to authentication and key generation schemes are enormous, specially in the field of portable devices. To have an entropy generator “in a chip” is great, if you get that together with a fingerprint of the chip is wonderful news. Certainly we’ll hear more about it.

 

Related reading: Quirks of RFID Memory Make for Cheap Security Scheme

 

ENIGMA encryption cracker Heroes

ENIGMA crackers reunite at Bletchley Park

I had the honour to meet one of them, now an emeritus math professor.

Check this article for pictures of the Turing Bombe the electronic-mechanical code-breaking machine used by the British to crack 3,000 Enigma messages a day during the Second World War.

Cryptool ver 1.4 has a very well done simulator of the ENIGMA machine encryption.