In this age of the multi-media, images have an important impact on communication. When users upload images over an insecure communication network, total security is a difficult problem to address in order to maintain image confidentiality. Also, encryption is a technique for keeping images secret. This study gives a basic introduction to cryptography, as well as a concise overview regarding the many image encryption algorithms' elemental security criteria. This paper includes an overview of several image encryption approaches as well as a comparison of discrete image encoding techniques, before coming to a conclusion and recommending future research.
The present paper builds a security system to encrypt and hide important text data. The system utilized an AES method to conduct an encryption process, followed by hiding the encrypted data using an improved Pixel Value Difference (PVD) technique. The method works to builds a map to hide data in a non-sequential way by relying on a hyperchaotic system to increase the security level. The system methodology proposed that the data embedding process is in one of the three levels of the colour image (Red, Green, and Blue), where the embedding level will determined based on the coordinates of the PVD pair points that is increase the efficiency of performance. A set of measures was used to measure the quality of steganography where we used MSE, PSNR, SNR, and Corr, and the results are well and satisfactory. The proposed method records the least MSE value with 0.85348784908256, while the Corr values did not decrease about 0.994145776227782. The proposed method also proved successful and effective in retrieving and decoding data, where the BER scale was equal to zero for all retrieved text.
Relational database management systems (RDBMS) emerged as the solution for data storage in the past decades. All data storage systems and applications utilize a RDBMS in the heart of the system to store and retrieve the data. In the past few years a new data storage model, named Not Only Structured Query Language (NOSQL), has emerged to produce less complex data storage systems and to tackle the data's massive volume performance degradation of used systems. In this work, a comparison study is conducted between MySQL as an example of RDBMS and Monogodb as an example of NOSQL systems using threading and machine resources to show the differences for developers to select one of these models for their applications. The results show that the performance of NoSQL is less than MySQL for small datasets and few database operations, such as few thousands of records and hundreds of operations per day. However, with the introduction of threads and volumes of data, the performance of Mongodb overcomes My Structured Query Language (MySQL). In addition, the results have shown that Mongodb requires more memory usage and CPU resources than MySQL to complete their tasks. Finally, the images were saved as byte data inside both platforms. The storing process for this data inside Mongodb was faster than the MySQL platform
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