Malware assaults on kernel rootkits have grown increasingly nuanced and difficult to detect, giving them control over the functionality of the kernel. It can be difficult to detect the presence of these kernel rootkits within the victim system since they use stolen techniques to conceal the system tasks, kernel modules, and various management structures. The majority of the current rootkit detection methods are system-specific and supported by traditional sources, making them ineffectual for new, obscure, and undiscovered rootkits. In order to identify such rootkits by their distinctive hidden processes, this study suggests a VKRHPDV system. This detection method uses a cross-view, clean-boot-based approach and defines a process-watching framework that continuously keeps track of all running processes and can identify any rumoured or unidentified rootkit with the least amount of performance overhead. The linguistics gap is filled by VKRHPDV, which monitors the kernel while extremely discretely intercepting call events of the tainted package to reconstruct a semantic-level method information structure. The results of an in-depth performance analysis performed on sixty-four rootkit datasets in a cloud environment for each UNIX and Windows kernel show that VKRHPDV can detect process hiding habits in all datasets in the shortest amount of time.