The development of the truly random numbers by two students at the University of Texas at Austin comes as a boost in the improvement of cyber security and data encryption. This is due to the generation of a random number with less computational efforts as compared to other methods. This is advantageous since it could significantly facilitate higher levels of security in the military communication as well as the consumer credit card transactions.
If it is to be implemented on the electronic voting system, for instance, we could see a more secure voting process. It could also play a huge role in conducting a statistically significant poll. That aside, given its complexity in structure, it could simulate with utmost accuracy, complex systems like the earth’s climate.
The random sequences
What’s fascinating about this new eCommerce development is that Eshan and Zukerman took two weakly random sequences which they turned into one random-number sequence. The weakly sequences like the stock market prices and air temperatures were conducted over time, and through such predictions, they were able to come up with a pattern.
It’s important to note that true random sequences hardly have any predictability and they can be compared to a toss of a coin. When the previous versions of the random number extractors were tested, they were seen to be less practical. This is because they required either of the two sequences to be truly random. It would also work if both of the sources sequences were close to truly random.
The Application of the random numbers
One of the key applications of the random number is the generation of keys that are used in data encryption. The encryption is highly secure that can make it harder for hackers to crack. Data encryption is also a key component when it comes to making secure bank transactions, shielding military communication from enemies, keeping medical data private, as well as making a secure credit card purchase.
Although there might be methods put in place to ensure the production of high-quality random numbers, the greatest challenge is that they tend to be computationally demanding. However, Zuckerman finds his method to produce high-quality random numbers. In so doing, if they can easily get access to high-quality random numbers then it could massively improve data security. The application comes at the right time given the threats faced in the cyber security space.
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