Computer scientists, including an Indian-origin student at the University of Texas at Austin, have developed a new method for producing truly random numbers – a breakthrough that can be used to encrypt data and improvecyber-security.
The new method creates truly random numbers with less computational effort than other methods, which could facilitate significantly higher levels of security for everything from consumer credit card transactions to military communications.
This can also make electronic voting more secure, conduct statistically significant polls, and more accurately simulate complex systems such as the Earth’s climate.
“This is a problem I have come back to over and over again for more than 20 years. I’m thrilled to have solved it,” said computer science professor David Zuckerman.
Zuckerman and graduate student Eshan Chattopadhyay publicly released a draft paper describing their method for making random numbers in an online forum.
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, harbour predictable patterns. Truly random sequences have nothing predictable about them, like a coin toss.
“When I heard about it, I couldn’t sleep,” said Yael Kalai, senior researcher working in cryptography at Microsoft Research New England. “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,” he added.
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.
“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 noted.
Zuckerman and Chattopadhyay will present their method at the annual Symposium on Theory of Computing (STOC) in Cambridge, Massachusetts, in June.