A Review of AI/ML Algorithms for Security Enhancement in Cloud Computing with Emphasis on Artificial Neural Networks

Security in cloud computing is becoming increasingly important due to the scale and sensitivity of data handled. Artificial Intelligence and Machine Learning algorithms offer robust solutions for enhancing security measures in cloud environments. Traditional security methods face challenges and the resilience to protect the loss of sensitive data and user privacy against emerging cyber threats. The use of Artificial Intelligence and Machine Learning is essential in the current era of big data era to handle and analyse enormous amount of cloud-based data quickly and accurately. In addition to the security challenges posed by cloud computing and Internet of Things (IoT) devices, the utilisation of AI by hackers remains an ongoing threat in the realm of cybersecurity. This paper review various Artificial Intelligence and Machine Learning algorithms, with a particular focus on the application of Artificial Neural Networks (ANNs). The paper review how ANN-based approaches contribute to improving threat detection, anomaly detection, access control, and encryption in cloud computing, highlighting their effectiveness and potential challenges. The paper reviews the benefits of ANNs and discusses the specific challenges faced in securing cloud computing systems. The implementation requirements of ANNs to enhance current approaches and overcome existing limitations.