Enhancing The Randomness Of Symmetric Key Using Genetic Algorithm

• Main Authors: Zakaria, Afiqah Zahirah, Ramli, Sofia Najwa, Wen, Chuah Chai, Mohd Foozy, Cik Feresa, Palaniappan, P. Siva Shamala, Othman, Nur Fadzilah
• Format: Article
• Language: English
• Published: Blue Eyes Intelligence Engineering and Sciences Publication 2019
• Online Access: http://eprints.utem.edu.my/id/eprint/24310/2/2.3.1.1%20JURNAL%20INDEKS%20SCOPUS%20-%20ENHANCING%20THE%20RANDOMNESS%20OF%20SYMMETRIC%20KEY.PDF; http://eprints.utem.edu.my/id/eprint/24310/; https://www.ijitee.org/wp-content/uploads/papers/v8i8s/H10550688S19.pdf

The focus of network security is to provide the secure, effective and private communication between the sender and the receiver. To achieve the aim of high security of sending information, the improvement in cryptography is needed to make sure the protection of the information against unauthorized users. Symmetric-key cryptography satisfies the constraint of resources in computational complexity performances, but it offers weak security since it is not resilient against physical compromise. One of the way to overcome the issue is by providing a cryptographic key that is strong, hard to break and almost unpredictable by the intruder. As the advancement of technology in Artificial Intelligence (AI), Genetic Algorithm (GA) is implemented to generate the best-fit key in symmetric-key cryptography. Due to natural selection of GA process, the generated key is found to be the most random and non-repeating as possible. Moreover, the fitness test shows the average fitness value of a generated key increases when the key length increases.