Cyber Security of Mobile Applications Using Artificial Intelligence

In recent years, the number of cyber-attacks has increased dramatically. Due to the widespread use of mobile devices, as well as the increasing popularity of mobile services, there are serious challenges in the field of cybersecurity. Traditional cybersecurity systems fail to detect malware and complex unknown attacks and do not guarantee user privacy is preserved. In the field of smartphone computing, artificial intelligence (AI) methods have expanded rapidly in recent years, often enabling devices to operate in an intelligent manner. Security against cyber-attacks on a large number of important mobile applications is a necessity in today's digital age. This paper presents how employees are using AI techniques to maintain cybersecurity in mobile applications using machine learning (ML), deep learning (DL), and artificial neural network (ANN). This paper describes an ANN to simulate a neuron in a mathematical equation, in which massive amounts of data are read to reach the desired result. ANNs are very useful in intrusion detection systems (IDS), mobile application security, and privacy breaches. We will also use supervised learning techniques in cybersecurity to identify malware and protect privacy.