The prediction is most important goals in economic quantitative studies, it basis in design and plan future economic policies properly process over forecasting accuracy. This paper is aiming at the problem salp swarm algorithm (SSA) for predicting grain yield is prone to fall into the local optimal problem. An improved SSA is proposed with combine with back propagation neural network. Using the different advantages of SSA algorithm in global search capabilities, combining the two for further optimize the weight, improve the accuracy and robustness of the grain yield prediction model. The specific implementation is selected from 1963 to 2013. These methods are used to define agricultural datasets that supports crop growth decision for grain product and its influencing factors were tested as a data set. The results show that, the improved salp swarm optimization can be classified as a good predict tool for the domestic food production trend in recent years compared with the SSA. This paper briefly introduces three artificial methods BP neural networks, SSA and improved SSA optimization algorithm. The natural behavior of salp, barrel-shaped plankton that are mostly water by weight optimization and combined with mixed-group of intelligent algorithm are simulated. The simulation results of grain production prediction illustrate that the predict precision of the improved SSA is much higher than of both conventional BPNN and SSA techniques and it’s very efficient and practicable.

Data protection is a complex problem affecting many areas including computers and communications. To ensure the necessary protection of applications, cryptographic methods and various algorithms are used. In this paper general overview of cryptography, information security and the comparison of algorithms with symmetric and asymmetric keys is presented. Factors ensuring the achievement of efficiency, flexibility and security are the basis of this research. As a result, the best solution for symmetric and asymmetric encryption is produced.

<p>A generalized model of information protection of a database management system is proposed, which can be used to implement database protection under any database management system. This model development methodology consists of four stages: requirements gathering, database analysis, “multi-level relational logical construction and a specific logical construction. The first three steps define actions for analyzing and developing a secure database, thus creating a generalized and secure database model”.</p>

The rapid developments observed in the field of Internet of Things (IoT), along with the recently increasing dependence on this technology in home and financial applications, have made it necessary to pay attention to the security of information sent through these IoT applications. The present article proposes a new encryption method for important messages that are sent via IoT applications. The proposed method provides four levels of security for the confidential message (in this case, an image). The first level is represented by applying the Conformal Mapping on the secret image. The second level is represented by encoding the resulting image from the first level using the encryption and decryption (RSA) method, while the third level is the use of Less Significant Bit (LSB) as the hiding method to hide the message inside the cover image. The compression of the stego image using GZIP is the last level of security. The peak signal-to-noise (PNSR) metric was used to measure the quality of the resulting image after the steganography process. The results appear promising and acceptable. Therefore, it is suggested that this method can be applied to send secret messages through applications of special importance across the IoT.

Modern telecommunication technologies play a decisive role in the methods of organization and structure of the construction of existing and projected mobile IAUs or specialized control systems designed to collect a given set of information about managed objects and, in accordance with the objective function, to manage these objects.