# A Finite State Machine-Based Improved Cryptographic Technique
###### Abstract  
With the advent of several new means of communication, safeguarding the confidentiality of messages has become more crucial. Financial institutions, virtual currencies, and government organizations are all examples of high-risk contexts where information exchanges need particular care. The importance of data security in preventing unauthorized access to data is emphasized. Several cryptographic methods for protecting the secrecy and integrity of data were compared. In this research, the proposed work includes a new Turbo Code-based encryption algorithm. The Turbo encoder's puncturing process is controlled by a secret key, and a typical random sequence is generated to encrypt the data and fix any mistakes. Key generation utilizing pre-existing data eliminates the requirement for sending keys over a secure channel. Using recurrence relations and the Lower-Upper (LU) decomposition method, the presented study suggests a novel approach to message encryption and decryption. The resulting encrypted grayscale image has a very high level of security, with an entropy of 7.999, a variation from perfection of 0.0245, and a correlation of 0.0092 along the diagonal, 0.0009 along the horizontal, and \(-\)0.0015 along the vertical. Directly decrypted pictures have a Peak Signal-to-Noise Ratio (PSNR) of 56.22 dB, but the suggested approach only manages an embedding capacity of 0.5 bpp (bits per pixel). This may be achieved by decreasing the size of the location map by only 0.02 bpp. Modified Cryptographic Turbo Code; Peak Signal-to-Noise Ratio; horizontal correlation; Finite State Machine  
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message (C). It is possible to encrypt the Plaintext (P) using a secret key (K) and decrypt it using the same key. Given the amount of rearranging and shuffling that took place, the connection between the ciphertext and the Plaintext is, at best, obscure. Subtly altering (P) by diffusion [2] sets the stage for the intricate interplay between neighboring symbols. The product cypher technique allows for bidirectional obfuscation and dissemination. The channel is used to send incoming messages to the source encoder with the best feasible data rate and accuracy [3]. The first encoder may read the symbols as code words. There is a unique coded message associated with every symbol. Before a source decoder can convert the output of a binary channel decoder back into a symbol sequence, it must first perform the inverse mapping of the source encoder's code words. Incorrect binary sequences may have been sent due to interference in the signal's path to its destination. Channel coding [4] methods are useful for eliminating this kind of mistake. Channel encoding involves an encoder at the transmitter end adding additional bits to the output of the source encoder using an al-algorithm. Information encoded in channel 1 might be decoded by a channel coding block decoder at the receiving end. Many error-correcting methods are used in channel encoding to ensure that the original bit sequence may be recovered in its entirety. Copyright protection and preventing malicious manipulation are the most pressing and difficult issues. Research suggests that keeping secrets might help alleviate these sorts of concerns. Covert data storage in media may be useful for a variety of purposes, such as facilitating the identification of images, safeguarding intellectual property, and regulating access. The integrity of the message would be compromised if information were distorted in a way that was not immediately obvious to the human eye. When dealing with overly sensitive information or medical imaging, even a little bit of inaccuracy might have serious consequences.