ABSTRACT
Applications related to security and privacy have made machine learning popular during the past 10 years. With the current volumes of so-called big data, manual processing is difficult and will be even more difficult in the future. To address this problem, machine learning has been implemented in a wide variety of technical computer science applications, particularly in big data processing and real-time decision-making applications to build quickly computed answers. A machine learning model is used to classify data with the greatest degree of accuracy. Machine learning techniques and algorithms come in a wide variety. The most recent study suggests that data-driven machine learning may be prone to security lapses, malware, and other problems. There are important privacy and information security issues that mobile systems and applications are addressing. This chapter explores the need for security and privacy in mobile technologies and demonstrates how crucial this issue is through technical improvements.
