Technology Dissertation Chapter Sample on The Strategy of Processing Data: Fuzzy Extractor and Randomness Extractor

The Strategy of Processing Data: Fuzzy Extractor and Randomness Extractor

When implementing a fuzzy extractor scheme, there are two critical aspects to consider; information reconciliation and privacy amplification. The noise generated from noisy data is removed in the Information reconciliation protocol (Maltoni 198). Similarly, uniform allotment derived key bits is guaranteed through Privacy amplification. Through a reliable data algorithm, noise and non-uniformity of the keys are seized by executing implementing information reconciliation in the initial phase and by applying a randomness extraction primitive in the second phase.

In Fuzzy Extractor Implementation, the syndrome construction secure sketch based on a concatenation of a binary repetition code assuming the inner code while binary BCH codes taking the outer code are deployed. Tistarelli, Massimo and Mark suggest, “The operation behaviors of the modified secure sketch are similar to that of the Hamming metric fuzzy extractor for location data” (121-122). These constructions differ in the amount of public information, decoding efficiency, and the degree of ease in practical implementation.  The appropriate fuzzy extractor construction should be applied depending upon the RF signals to implement geo-security, computational power, and the user’s decision on the FRR-FAR tradeoff.

The BCH codes come from an efficient unit of linear block codes through which a proficient decoding algorithms is acquired. Binary BCH codes with parameters [nBCH, kBCH, tBCH] are defined for nBCH=2u-1, but through the use of code word shortening. From this dimension, attaining a BCH code of any length is very possible. Any comparison assumes that the generic BCH decoder exists, thus allowing decoding of code length up to nBCH=2047. For a hardware design, this is a reasonable estimation. The output of the practical fuzzy extractor is the running hash value of the recovered fuzzy inputs (Holz, Thorsten, and Sotiris Ioannidis 219).

A HIS based product integrates readout mechanism of an electronic fingerprint into a secure, reliable, and economically attractive implementation of a security solution. Counter attack measures are developed and implemented in the HIS to provide a layered, in-depth security approach. The cryptographic engineering of a PUF-based authentication protocol necessitates a concrete proof. Finally, primary PUF based protocol designs take the form of perfect PUF operations. “They make abstraction of complex noise effects that come with real PUF” (Maes 279). The actual performance actual performance of these protocols and designs, and often their implementation cost, remain unknown. 

Work Cited

Holz, Thorsten, and Sotiris Ioannidis. Trust and Trustworthy Computing: 7th International Conference. Trust 2014, Heraklion, Crete, Greece, June 30-July 2, 2014: Proceedings.  2014. Internet resource.

Maes, Roel. Physically Unclonable Functions: Constructions, Properties and Applications. Berlin, Heidelberg: Imprint: Springer, 2013. Internet resource.

Maltoni, Davide. Handbook of Fingerprint Recognition. New York: Springer, 2009. Print.

Tistarelli, Massimo, and Mark S. Nixon. Advances in Biometrics: Third International Conference, Icb 2009, Alghero, Italy, June 2-5, 2009 : Proceedings. Berlin [etc.: SpringerLink [host, 2009. Print.