Cloud computing is a long-standing dream of computing as a utility, where users can store their data remotely in the cloud to enjoy on-demand services and high-quality applications from a shared pool of configurable computing resources. Thus, the privacy and security of data are of utmost importance to all of its users regardless of the nature of the data being stored. In cloud computing environments, it is especially critical because data is stored in various locations, even around the world, and users do not have any physical access to their sensitive data. Therefore, we need certain data protection techniques to protect the sensitive data that is outsourced over the cloud. In this paper, we conduct a systematic literature review (SLR) to illustrate all the data protection techniques that protect sensitive data outsourced over cloud storage. Therefore, the main objective of this research is to synthesize, classify, and identify important studies in the field of study. Accordingly, an evidence-based approach is used in this study. Preliminary results are based on answers to four research questions. Out of 493 research articles, 52 studies were selected. 52 papers use different data protection techniques, which can be divided into two main categories, namely noncryptographic techniques and cryptographic techniques. Noncryptographic techniques consist of data splitting, data anonymization, and steganographic techniques, whereas cryptographic techniques consist of encryption, searchable encryption, homomorphic encryption, and signcryption. In this work, we compare all of these techniques in terms of data protection accuracy, overhead, and operations on masked data. Finally, we discuss the future research challenges facing the implementation of these techniques.

With the development of the Industrial Internet of Things (IIoT), the amount of data generated by industrial manufacturing equipment is growing rapidly, creating a critical need for secure and efficient cloud-based data sharing. While bilateral access control enables both data senders and receivers to define their own fine-grained access policies, existing schemes transmit these policies in plaintext, exposing sensitive operational metadata and creating security vulnerabilities. Furthermore, they lack essential functionalities for practical IIoT deployment, including efficient duplicate data detection, a robust user revocation mechanism, and computationally lightweight operations suitable for resource-constrained devices. To address these challenges, this article proposes a novel policy-hiding, lightweight, and revocable bilateral access control scheme with equality test (RBAC-ET) for cloud-enabled IIoT systems. RBAC-ET is the first scheme to integrally combine five critical capabilities: first, fine-grained bilateral access control using linear secret sharing schemes (LSSSs) supporting and/or logical operations. Second, policy confidentiality is achieved by encrypting access policies within the ciphertext to prevent the leakage of sensitive relationships. Third, the equality test functionality enables cloud servers to identify duplicate ciphertexts for efficient storage and processing without requiring decryption. Fourth, a proposed lightweight design is based on elliptic curve scalar multiplication operations instead of the more resource-intensive bilinear pairing operations. Fifth, a robust user revocation mechanism that ensures both forward and backward secrecy in dynamic industrial environments. Theoretical analysis and experimental results demonstrate that RBAC-ET offers superior security and functionality while maintaining computational efficiency comparable to that of state-of-the-art schemes, making it a scalable and practical solution for modern IIoT data-sharing applications.