In this paper, a new Playfair cipher built on bits level symmetric key cryptographic was proposed for the purpose of converting pairs of letters (digraphs) into single letters. The proposed algorithm is capable to overcome many of the shortcoming and vulnerabilities that exist in the current classical version of Playfair algorithm. The Playfair cipher is exceedingly complex than a classical substitution cipher, but still simple to hack using automated tactics. It is famous as a digraph cipher because two letters are exchanged by other two letters. This destroys any solo letter occurrence statistics, but the digraph statistics still unaffected (frequencies of two letters). Unluckily letter pairs have a flatter distribution than the one letter frequencies, so this intricacy matters for solving the code using pen and paper procedures. The suggested encryption process is conducted as follows; letters are first arranged in a spiral manner in Polybius square, afterwards, each pair will be replaced utilizing before-after technique if we are arranging pairs horizontally and down-up technique (vertically). The former process produces pairs of Plaintext that will be converted to binary bit stream then will be divided over blocks with stable sizes. Bits of these blocks are taken from pairs then fit them into square matrix of suitable order to put the concept of row-wise and revers row-wise matrix. Bits of this matrix are split into 2x2 square matrixes. The sub-matrixes are formed 8 bits. Here the XNOR operation is taken into consideration for bitwise operation to generate the keys for decryption and produce the cipher-text.

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Metaheuristic algorithms are becoming powerful methods for solving continuous global optimization and engineering problems due to their flexible implementation on the given problem. Most of these algorithms draw their inspiration from the collective intelligence and hunting behavior of animals in nature. This paper proposes a novel metaheuristic algorithm called the Giant Trevally Optimizer (GTO). In nature, giant trevally feeds on many animals, including fish, cephalopods, and seabirds (sooty terns). In this work, the unique strategies of giant trevally when hunting seabirds are mathematically modeled and are divided into three main steps. In the first step, the foraging movement patterns of giant trevallies are simulated. In the second step, the giant trevallies choose the appropriate area in terms of food where they can hunt for prey. In the last step, the trevally starts to chase the seabird (prey). When the prey is close enough to the trevally, the trevally jumps out of the water and attacks the prey in the air or even snatches the prey from the water surface. The performance of GTO is compared against state-of-the-art metaheuristics for global optimization on a set of forty benchmark functions with different characteristics and five complex engineering problems. The comparative study, scalability analysis, statistical analysis based on the Wilcoxon rank sum test, and the findings suggest that the proposed GTO is an efficient optimizer for global optimization. Note that the MATLAB source codes for GTO will be publicly available after the acceptance of the paper.

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