Dynamic VM Surveillance and Encrypted Access Control For Cloud Workload Protection
TL;DR
Comparative study is presented using different graph representations of file size and timing of encryption, in which efficient SRM can be achieved only within a limited context, to showcase the feasibility and success of the proposed strategies for using resources securely in real-time cloud infrastructure protection.
Abstract
Secure Resource Management (SRM) is crucial in cloud computing environments that share resources across virtual machines (VMs) and have potential attack surfaces for malicious actions. A lack of use of resources may compromise system integrity and lead to undesirable access. To address this problem, threat countermeasures are categorised into 3 strategies, namely defense, mitigation and hybrid, through a meta-analytical approach. To stop incursions, defensive tactics implement strong access control, AES-based encryption, and vulnerability management. The primary concerns of mitigating techniques are monitoring, incident handling and controlled use of files with significant validation procedures. AI-driven adaptive monitoring is included into hybrid techniques to instantly identify and stop unauthorized virtual machine activity. The lightweight Speck cipher technique, which is more computationally efficient than AES, is also used to lower encryption delay and check data integrity using file-hash associations. Comparative study is presented using different graph representations of file size and timing of encryption, in which efficient SRM can be achieved only within a limited context. The methodology is validated with simulated cloud and virtual machine environments to showcase the feasibility and success of the proposed strategies for using resources securely in real-time cloud infrastructure protection.