ObjectiveStudy and test the existing Pseudorandom Number Generators uAbstract:Language Platform, and CompilerInput/Output SpecificationFunctionalityProceduresTestingScheduleMarch 5, 2005 Submission of first draft of specification.March 12, 2005 Submission of final project specificationMarch 29, 2005 First Progress ReportMay 3, 2005 Third Progress ReportDraft version of Final PresentationMay 9, 2005 Draft version of the final written reportMay 12, 2005 Review of a draft report of another team duePossible Changes in SpecificationReferencesStatistical Tests for Randomness Chandrika Lanka Harini Vasudevan Swetha Manne Objective Study and test the existing Pseudorandom Number Generators using public domain implementation of NIST Statistical Test Suite and integrate the results with KRYPTOS Educational Software. Abstract: The need for random and pseudorandom numbers arises in many cryptographic applications like generation of session keys, initialization vectors and creation of public keys. The security of cryptographic systems depends on the generation of unpredictable numbers. Although several tests exist to evaluate the Pseudorandom Number Generators (RNGs), such as the 16 tests in the NIST Statistical Test Suite, correct interpretation of probabilistic results is critical for final assessment of RNGs. Apart from testing and evaluation of existing PRNGs, our major goal would be good interpretation of test results and integration with KRYPTOS for educational purposes. Language Platform, and Compiler NIST Statistical Test Suite package Specification: Language: ANSI C Operating System: SunOS Compiler: ANSI C Compiler Portability: Platform independent, but minor modifications to be incorporated when ported to other platforms. Successfully ported to SGI Origins and onto IBM PC under Windows 98 and Microsoft C++ 6.0. We plan to modify the code to work under Windows XP with Microsoft C++. Input/Output Specification Input: file of arbitrary length containing binary sequences to be tested for randomness. Output: Assessment (Pass/Fail) made from results of an output file. (The output file has results in the form of logs of empirical results that correspond to the computational information) Functionality The package performs the selected tests on the user prescribed input and produces a file with proportion of passing sequences for each test and a pass/fail assignment.Procedures • The initial step is to download the source code and test it for portability. • Learn about the working of Random number Generators and Pseudorandom generators. (This test suite has implementations of nine PRNGs) • Apply Strategy of statistical analysis of RNGs specific to the NIST Test Suite and present an assessment. • Integrate the test source code with KRYPTOS with input as file of binary sequences and selection of tests, and output in the form of an assessment report of random sequence. Testing The results of tests can be compared with sample data of test results of existing RNGs to prove the validity of the tests results. Schedule March 5, 2005 Submission of first draft of specification. March 12, 2005 Submission of final project specification March 19, 2005 Testing the code for portability on the intended platform complete. Study working of PRNGs and relation of statistical tests to cryptography. March 26, 2005 Initial run of the code with existing PRNGs and inspection of sample results March 29, 2005 First Progress Report Detailed presentation of format of input and output functions Results of statistical analysis of half of the existing PRNGs. April 19, 2005 Second Progress Report Detailed presentation of validity of results of statistical analysis of all the remaining PRNGs. Initiate work on integration with KRYPTOS. April 26, 2005 Integration with KRYPTOS complete. May 3, 2005 Third Progress Report Draft version of Final Presentation May 9, 2005 Draft version of the final written report May 12, 2005 Review of a draft report of another team due May 13, 2005 Discussion of the project reports and viewgraphs with the instructor; the instructor’s recommendations for revisions. May 17, 2005 Final oral presentations, final project reports submitted through WebCT.Possible Changes in Specification • Platform and Compiler: this may change depending on portability test results. • Testing of all the pseudorandom generators may not be included due to time constraints. • References References Introduction and Surveys [1] “Random number generation,” in The Handbook of Simulation, pp. 93-137. Wiley, New York, 1998. [2] J. E. Gentle, W. Haerdle, and Y. Mori, “Random Number Generation” in the draft for a chapter of the forthcoming Handbook of Computational Statistics, Ed. Springer-Verlag, 2004. [3] P. 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