A High Security Symmetric Key Generation by Using Genetic Algorithm Based on a Novel Similarity Model

Abstract

Encryption technology has a great influence on data security. There are many encryptions have been proposed. In general, the encryptions with higher complexity will provide higher security, but it will also consume a lot of computing resources. In some cases, these high complexity method may not suitable such as Internet of Thing devices. This is because Internet of Thing device has lower computing power due to the size and the limited battery. Therefore, most of Internet of Thing (IoT) devices are used symmetric encryption as the main method. However, this kind of symmetric encryption algorithms are easy to occur weak keys such as data encryption algorithm (DES). This will expose IoT devices to high risk environments. In this study, a new fitness function has given and then a Genetic Algorithm-based symmetric key generation is proposed. As the simulation results, our proposed method can provide higher randomness and very low probability to occur the weak keys so that the data security in IoT environment will be increased significantly.