This new method generates truly random numbers

"When I heard about it, I couldn't sleep," says Yael Kalai of Microsoft Research New England who has also worked on randomness extraction. "I was so excited. I couldn't believe it. I ran to the (online) archive to look at the paper. It's really a masterpiece." (Credit: iStockphoto)

Computer scientists have developed a new method for producing truly random numbers, a breakthrough that could be used to encrypt data, make electronic voting more secure, conduct statistically significant polls, and more accurately simulate complex systems such as Earth’s climate.

The method creates the random numbers with less computational effort than others, which could make it easier to offer significantly higher levels of security for a variety of applications, including consumer credit card transactions and military communications.

“This is a problem I’ve come back to over and over again for more than 20 years,” says David Zuckerman, a computer science professor at the University of Texas at Austin. “I’m thrilled to have solved it.”

The new method takes two weakly random sequences of numbers and turns them into one sequence of truly random numbers. Weakly random sequences, such as air temperatures and stock market prices sampled over time, harbor predictable patterns. Truly random sequences have nothing predictable about them, like a coin toss.

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Previous versions of randomness extractors were less practical because they either required that one of the two source sequences be truly random (which presents a chicken or the egg problem) or that both source sequences be close to truly random. This new method sidesteps both of those restrictions and allows the use of two sequences that are only weakly random.

An important application for random numbers is in generating keys for data encryption that are hard for hackers to crack. Data encryption is critical for making secure credit card purchases and bank transactions, keeping personal medical data private, and shielding military communications from enemies, among many practical applications.

“When I heard about it, I couldn’t sleep,” says Yael Kalai, a senior researcher working in cryptography at Microsoft Research New England who has also worked on randomness extraction. “I was so excited. I couldn’t believe it. I ran to the (online) archive to look at the paper. It’s really a masterpiece.”

Although there are already methods for producing high-quality random numbers, they’re computationally demanding. The new method produces higher quality randomness with less effort, Zuckerman says.

“One common way that encryption is misused is by not using high-quality randomness. So in that sense, by making it easier to get high-quality randomness, our methods could improve security.”

Zuckerman and graduate student Eshan Chattopadhyay will present their research in June at the annual Symposium on Theory of Computing.

Source: University of Texas at Austin