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Science

SITE VISIT: Pick a Number From 1 to 232

Published Jul 7, 2000• 0 citations
Publisher

Abstract

From encrypting e-mail messages to simulating the collapse of stars, many scientific procedures require random numbers. But generating truly random numbers with a computer is impossible. Computers can only follow algorithms, and no matter how convoluted, an algorithm tells you how to get the next number from all the preceding ones. Mother Nature, however, is less predictable, and three Web sites rely on quirky physical processes to provide the truly random bits you crave.

DOI
10.1126/science.289.5476.7b

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From encrypting e-mail messages to simulating the collapse of stars, many scientific procedures require random numbers. But generating truly random numbers with a computer is impossible. Computers can only follow algorithms, and no matter how convoluted, an algorithm tells you how to get the next number from all the preceding ones. Mother Nature, however, is less predictable, and three Web sites rely on quirky physical processes to provide the truly random bits you crave.
Randomness is crucial for a variety of applications, ranging from gambling to computer simulations, and from cryptography to statistics. However, many of the currently used methods for generating randomness do not meet the criteria that are necessary for these applications to work properly and safely. A common problem is that a sequence of numbers may look random but nevertheless not be truly random. In fact, the sequence may pass all standard statistical tests and yet be perfectly predictable. This renders it useless for many applications. For example, in cryptography, the predictability of a randomly" chosen password is obviously undesirable. Here, we review a recently developed approach to generating true | and hence unpredictable | randomness.
Abstract Random number generation (RNG) is needed for a myriad of applications ranging from secure communication encryption to numerical simulations to sports and games. However, generating truly random numbers can be elusive. Pseudorandom bit generation using computer algorithms provides a high random bit generation rate. Nevertheless, the reliance on predefined algorithms makes it deterministic and predictable once initial conditions are known. Relying on physical phenomena (such as measuring electrical noise or even rolling dice) can achieve a less predictable sequence of bits. Furthermore, if the physical phenomena originate from quantum effects, they can be truly random and completely unpredictable due to quantum indeterminacy. Traditionally, physical RNG is significantly slower than pseudorandom techniques. To meet the demand for high‐speed RNG with perfect unpredictability, semiconductor light sources are adopted as parts of the sources of randomness, i.e., entropy sources, in quantum RNG (QRNG) systems. The high speed of their noise, the high efficiency, and the small scale of these devices make them ideal for chip‐scale QRNG. Here, the applications and recent advances of QRNG are reviewed using semiconductor emitters. Finally, the performance of these emitters is compared and discuss their potential in future technologies.
Alice and Bob want to flip a coin by telephone. (They have just divorced, live in different cities, want to decide who gets the car.) Bob would not like to tell Alice HEADS and hear Alice (at the other end of the line) say "Here goes . . . I'm flipping the coin. . . . You lost!"Coin-flipping in the SPECIAL way done here has a serious purpose. Indeed, it should prove an INDISPENSABLE TOOL of the protocol designer. Whenever a protocol requires one of two adversaries, say Alice, to pick a sequence of bits at random, and whenever it serves Alice's interests best NOT to pick her sequence of bits at random, then coin-flipping (Bob flipping coins to Alice) as defined here achieves the desired goal:1. It GUARANTEES to Bob that Alice will pick her sequence of bits at random. Her bit is 1 if Bob flips heads to her, O otherwise.2. It GUARANTEES to Alice that Bob will not know WHAT sequence of bits he flipped to her.Coin-flipping has already proved useful in solving a number of problems once thought impossible: mental poker, certified mail, and exchange of secrets. It will certainly prove a useful tool in solving other problems as well.
Randomness property is an essential component in fields of cryptography, scientific simulations, secure communications and randomized algorithms. In this study, the reason for pseudo random generators were analyzed and illustrated for which are being slowly replaced by quantum random number generators. Quantum mechanics has emerged as a domain with extreme potential, however, the biggest challenge being faced towards practical utilization is that of scalability. This study proposes a method for Truly Random Bit Sequence (TRBS) generation also determining the most suitable physical implementation of qubits in the process for application in domains of data security, integrity and authentication as a precursor to secure communications. Illustration of the proposed method reaffirms that the probabilistic nature of quantum measurement and inherent randomness being used for the sequence generation lead to a truly random sequence which is also validated through NIST testing suite results.