Cryptography is a method for preventing illegitimate access to information and data. In this paper, a bio-inspired cryptographic DNA system has been proposed. The proposed method consists of three phases: encryption, key generation and decryption. The scheme is proposed, from reproducing the normal procedures in the genetic encoding, transcription and translation and some of the inverse procedures have been used for the encryption and decryption of the data. And also for the encryption and decryption algorithms, it concentrates on the Central Dogma of Molecular Biology (CMDB).Thus, to store in the memory storage, a Bidirectional Associative Memory Neural Network (BAMNN) is used by recognizing and restoring the set of keys in present mode, and it is used educated in the randomized important generation information. Here, Whale Optimization Algorithm (WOA) is the highest fit weight vector. The proposed bio-instrumented encrypting system consists of adequate encoding as well as the decryption times, even though when the data is correlated in larger sizes in the current systems. Different safety attacks analyze the efficiency of the cryptosystem. This paper explored efficiency of the WOA algorithm by changing the number of hidden and input neurons. The proposed method is compared with traditional cryptographic techniques results in 55 and 67% increased processing time for encryption process and decryption process respectively.

密码学是一种防止非法访问信息和数据的方法。在本文中，提出了一种仿生加密 DNA 系统。所提出的方法包括三个阶段：加密、密钥生成和解密。提出该方案，从遗传编码、转录和翻译中的正常程序的再现和一些逆程序已被用于数据的加密和解密。并且对于加密和解密算法，它专注于分子生物学的中心法则（CMDB）。 因此，将双向关联记忆神经网络（BAMNN）存储在内存中，通过识别和恢复密钥集在目前的模式下，它被用于随机化重要世代信息的教育。这里，鲸鱼优化算法 (WOA) 是最高拟合权重向量。所提出的生物仪器加密系统由足够的编码和解密时间组成，即使在当前系统中数据以较大尺寸相关时也是如此。不同的安全攻击分析密码系统的效率。本文通过改变隐藏和输入神经元的数量来探索 WOA 算法的效率。所提出的方法与传统的密码技术相比，加密过程和解密过程的处理时间分别增加了 55% 和 67%。不同的安全攻击分析密码系统的效率。本文通过改变隐藏和输入神经元的数量来探索 WOA 算法的效率。所提出的方法与传统的密码技术相比，加密过程和解密过程的处理时间分别增加了 55% 和 67%。不同的安全攻击分析密码系统的效率。本文通过改变隐藏和输入神经元的数量来探索 WOA 算法的效率。所提出的方法与传统的密码技术相比，加密过程和解密过程的处理时间分别增加了 55% 和 67%。