Secured Cloud APIs Using Activity Analyzer

Abstract

Application programming interfaces (APIs) are a framework provided by cloud computing providers for managing and accessing cloud services. Security risks might be caused by these APIs. For access to cloud resources and services, developers using APIs require authentication credentials. If an unauthorized user obtains credentials, a serious threat can arise. The likelihood of engaging in risky behavior is therefore very high. To safeguard the cloud environment, numerous studies of security models have been carried out. Building a model for safety in identifying and measuring abnormal (unsafe) activities remains difficult and scalable due to behavioral complexity. This paper proposed an automated model for analyzing API activity for detecting and measuring any unsafe behavior of API based on various metrics. The analyzer takes an appropriate response when detecting any abnormal API activity. According to several measures, the experiments showed that the proposed model improved cloud security and blocked unsafe activities.