WASHINGTON: Researchers, including one of Indian-origin, have developed a new method for producing truly random numbers – a breakthrough that could be used to encrypt data and improve cybersecurity.
Computer scientists at the University of Texas at Austin developed the method that can be used to make electronic voting more secure, conduct statistically significant polls and more accurately simulate complex systems such as Earth’s climate.
The 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.
The new method developed by Professor David Zuckerman and graduate student Eshan Chattopadhyay 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.
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, researchers said.
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, researchers said.
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.
Zuckerman said that although there are already methods for producing high-quality random numbers, they are very computationally demanding. His method produces higher quality randomness with less effort.
“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,” said Zuckerman.