Abstract:

Nowadays, the successful transmission of data between end users, data protection and confidentiality are important issues. In our study, a system that ensures the transmission of bitwise encrypted images in pixel color matrix information based on the Lehmer algorithm for the generation of random keys over an end-to-end reliable communication channel and guarantees accuracy validation has been created. Using the deep learning model, metadata is created with the properties of the detected objects in the image scene. In the study, structured data is created in Base64 encoding format after encryption is done by the sender end of the message using the Lehmer algorithm. This message is transmitted end-to-end to the receiving party over the secure transmission channel. Finally, the encoded version of the image and the metadata information are extracted from the structured data exchange and transfer file containing the detection information of the objects in the image scene in the message packet reaching the receiver end, and also, decryption is performed. On the receiver end, object detection results of the deep learning model are compared with the decrypted information obtained from this file, and an objective verification of the accuracy of the message is also performed. Considering the average values in the experiments, the average values with the data obtained from three different data sets are for the Number of Pixels Change Rate (NPCR) 99.61%, the Unified Average Changing Intensity (UACI) 14.70%, and also, the maximum average entropy value is obtained 7.9999 for encrypted images. In our study, discussions and evaluations based on scientific findings are included.

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