Thesis (M. Phil.)--University of Hong Kong, 2009. / Includes bibliographical references (leaves 61-66) Also available in print.

Thesis (Ph. D.)--Rutgers University, 2007. / "Graduate Program in Mathematics." Includes bibliographical references (p. 64-65).

Information in the form of online multimedia, bank accounts, or password usage for diverse applications needs some form of security. the core feature of many security systems is the generation of true random or pseudorandom numbers. Hence reliable generators of such numbers are indispensable. the fundamental hurdle is that digital computers cannot generate truly random numbers because the states and transitions of digital systems are well understood and predictable. Nothing in a digital computer happens truly randomly. Digital computers are sequential machines that perform a current state and move to the next state in a deterministic fashion. to generate any secure hash or encrypted word a random number is needed. But since computers are not random, random sequences are commonly used. Random sequences are algorithms that generate a pattern of values that appear to be random but after some time start repeating. This thesis implements a digital random number generator using MATLAB, FGPA prototyping, and custom silicon design. This random number generator is able to use a truly random CMOS source to generate the random number. Statistical benchmarks are used to test the results and to show that the design works. Thus the proposed random number generator will be useful for online encryption and security.

Information in the form of online multimedia, bank accounts, or password usage for diverse applications needs some form of security. the core feature of many security systems is the generation of true random or pseudorandom numbers. Hence reliable generators of such numbers are indispensable. the fundamental hurdle is that digital computers cannot generate truly random numbers because the states and transitions of digital systems are well understood and predictable. Nothing in a digital computer happens truly randomly. Digital computers are sequential machines that perform a current state and move to the next state in a deterministic fashion. to generate any secure hash or encrypted word a random number is needed. But since computers are not random, random sequences are commonly used. Random sequences are algorithms that generate a pattern of values that appear to be random but after some time start repeating. This thesis implements a digital random number generator using MATLAB, FGPA prototyping, and custom silicon design. This random number generator is able to use a truly random CMOS source to generate the random number. Statistical benchmarks are used to test the results and to show that the design works. Thus the proposed random number generator will be useful for online encryption and security.

Several pseudorandom number generators are described and compared on the basis of cost of generation and length of period of the sequences that are produced. The major statistical tests, which are used to obtain a measure of randomness for the different generators are discussed and compared. Four pseudorandom number generators are programmed in GPSS and are used to generate interarrival and service times for an M/M/1 queuing system. The results of each of the trials are compared to the theoretical results which can be obtained from queuing theory.

Random numbers are a basic part in a Simulation Model, and they are also used in random sampling. These techniques are employed by quality engineers in the successful execution of their jobs. The every-day use of random numbers, however, often leads to a sense of complacency in he mind of engineers toward the exacting requirements that should be satisfied by the random number process to generate a genuine random number. Microcomputers have become a common and powerful tool that helps managers and engineers in their simulation experiments by providing sequences of random numbers. This research presents a sequence of eight tests to test the Radio Shack microcomputer system random number generator for uniformity and randomness; then, this Radio Shack random number generator is used to generate uniform and non-uniform deviates and a non-parametric test is performed to test these deviates for randomness. Two computer programs written in the BASIC language are used to test for randomness. The first one to test the Radio Shack random number generator and the second one to test the uniform and non-uniform deviates.

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