Improved algorithms are here to protect your data!
In this 21st century, the most valuable thing in the world is data. That is why data security firms and applications are in great demand nowadays. Various algorithms, create the baseline for data security. Cryptography is such a technology that is more in use now in the business. This technology can estimate the level of security that an algorithm can ensure. Recently a team of researchers from Daegu Gyeongbuk Institute of Science and Technology (DGIST), Korea developed such an algorithm. This algorithm has the ability to measure the difficulty level that any hacker should face to decrypt it. Their research just got published in the IEEE Transactions on Information Forensics and Security.
Cryptography,algorithms and this research
Cryptography is a technique by which communication is made secure. Generally, cryptography means certain protocols that prevent the third party from reading a private message. With the development and advancement of computers, cryptography methods have become increasingly complex. The algorithms are designed around computational hardness, making those hard to break in practice. In a simple example, cryptographic algorithms generate random numbers. Anyone to read the data or hack it, need to correctly predict and find that numbers.
Scientists use a metric, called the ‘min-entropy to estimate and validate a source as a random numbers generator. According to scientist Yongjune Kim, “the randomness of the produced random number is crucial for the security of cryptographic systems.” Data secured with low entropy is easier to decrypt and vice versa. In practice, correct estimation of the min-entropy is very difficult. Kim and his team developed an algorithm that estimates the min-entropy.
What is new in this research?
The algorithm works in offline mode. Along with an online estimator, that algorithm estimates the min-entropy with limited data. The estimation improves with increasing data sets. One advantage of their innovation is that it consumes very little energy. Kim says, “this algorithm can estimates min-entropy 500 times faster than the standard algorithms with excellent accuracy.” Currently, the team is working to improve the accuracy of the estimation.