# RACHEM: Reinforced Reliable Computing in Cloud by Ensuring Restricted Access Control
### Cloud Security  
Cloud computing follows a data-centric model, where securing data storage, transmission, and access is of paramount importance. The cloud is home to numerous machine clusters for providing computing power. The cloud infrastructure enables the allocation of virtually provisioned resources requested by the customer. A centralized controller module helps in maintaining efficient communication between the customer and the service provider. An illustrative representation of the computing and data-centric model for cloud computing services is provided in Figure 1.  
The data-centric approach in cloud computing can be broadly categorized into intra-data center and inter-data center models. In the intra-data center model, services provided to customers are hosted within a single, centralized data repository. Conversely, the inter-data center model involves the distribution of cloud services and resources across multiple data centers, all managed by a single CSP. In both cases, the responsibility for ensuring data security at the cloud end lies primarily with the service provider. Cloud security encompasses a comprehensive set of procedures, tools, policies, and controls designed to protect data, applications, and infrastructure hosted within cloud environments. It is essential for addressing internal and external threats that target diverse business models, such as Business-to-Business (B2B) and Business-to-Customer (B2C). As organizations and individuals increasingly depend on cloud services to store, process, and access sensitive information, ensuring the security and privacy of cloud-hosted resources becomes paramount. Cloud security includes key components such as data protection, access control, regulatory compliance, and threat mitigation. Among the major challenges in cloud security are the prevention of unauthorized access and the maintenance of data confidentiality. Data breaches remain a significant concern, as they compromise the integrity and reliability of user data while also damaging the trust relationship between Service Users (SUs) and Service Providers (SPs). Recent high-profile breaches [1; 2; 3] have resulted in the exposure of sensitive user credentials, affecting thousands of users. According to an IBM study [4; 5; 6], global financial losses due to data breaches are projected to rise to USD 10.5 trillion by 2025. Therefore, it is imperative  
Figure 1: Data centric computing model for cloud. to strengthen existing Intrusion Detection Systems (IDS) and enforce strict compliance in cloud configurations to ensure that only verified users are granted access to sensitive data. Among these measures, access control plays a critical role by defining and enforcing the rules for who can access specific data, resources, and applications in the cloud. The traditional RBAC models [7; 8; 9; 10] are less effective in validating the user role credentials for granting access permissions. These models assign permissions to roles and roles to users. However, they often do not include strong cryptographic methods to validate whether a user genuinely possesses a particular role at the time of access request. For instance, the work illustrated in [7] focuses more on attributes rather than verifying role credentials linked to a user identity in real time. The research in [10] attempts to implement RBAC using Attribute-Based Encryption (ABE), but it predominantly maps roles to attributes without incorporating robust authentication of user role bindings through cryptographic credentials such as role secrets. Furthermore, models like those in [7; 10] define access policies at the point of data encryption using ABE. However, these policies are static and inflexible, making it challenging to adapt to dynamic scenarios involving role changes, revocations, or temporary privilege grants--common in modern cloud computing environments.