Optimizing Performance and Security in Information Systems by Adopting Artificial Intelligence and Data Analysis

Authors

  • Jonathan Gabriel Crespo Moran, Gladys Geoconda Esquivel Paula, Johnny Xavier Bajaña Zajia

Keywords:

Optimization, Information Systems, Wireless Networks, Performance, Security, Artificial Intelligence; Machine Learning; Deep Learning

Abstract

The use of artificial intelligence (AI) techniques and deep learning based on data analysis for the design and management of emerging communication networks is justified by the increasing complexity of communication systems, conditioned by the diversity of technologies, services, and use cases with different technical requirements. This study is a documentary review that describes the usefulness of artificial intelligence and data analysis to improve both performance and security in information systems, presenting a trend in the present day of countless scientific contributions of AI and its application in wireless communication systems. Traditionally, the classical way of studying improvement has focused on the performance of wireless transceivers under the paradigm of dividing and conquering signals. The paradigm shift comes from artificial intelligence, which has been used to improve real-time wireless communication by analyzing previous data and user preferences. In addition to combining information security with its overall capabilities for risk management, virus prevention, and intrusion detection, it is intended to establish that by unlocking the potential of a wireless network orchestrated by the use of AI, it is possible to maximize resource use and minimize costs, requiring access to and analysis of large amounts of network data. Therefore, continuous updating of data is important for building successful and efficient wireless communication systems.

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06.08.2024

How to Cite

Jonathan Gabriel Crespo Moran. (2024). Optimizing Performance and Security in Information Systems by Adopting Artificial Intelligence and Data Analysis. International Journal of Intelligent Systems and Applications in Engineering, 12(23s), 705 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6979

Issue

Section

Research Article