With the advent of Cloud-storages, secure sharing of encrypted data with fine-grained access control has become an important challenge. To enforce fine-grained access rights on encrypted data to different users, Attribute-Base Encryption (ABE) is a promising cryptographic tool. But in many situations, some pirate users sell their access privileges for monetary gain. Hence, an efficient Black-Box Traitor Tracing (BB-TT) system is vital to address the corresponding Pirate Decoders (PDs). But, in the existing BB-TTs, the tracing complexity is directly related to the maximum number of users in the system. This paper proposes an ABE-based access control system that provides a new Relaxed BB-TT. Our Relaxed BB-TT addresses the complexity problem by exploring the pirate user with an optimal number of decryption queries on the PD. The optimal number of queries leads to the exciting capability of traceability of stateful decoders (i.e., the decoder that can save the states among theTracer's queries). Finally, our system provides White-Box traceability and reduces the amount of trust in the authorities. We give formal security proofs and extensive experimental results on different classes of mobile devices, including a laptop and a smartphone.

The Edge-Fog-Cloud interplay in the Internet-of-Things (IoT) leads to many exciting data-sharing applications that use access control systems as primary requirements. To ensure a fine-grained data access control for such data-sharings on untrusted storage (e.g., Cloud), Attribute-Based Encryption (ABE) is a promising tool. To address privacy concerns in such ABE-based access control systems, we propose a new Privacy-preserving Distributed data Access control (PDAC) in CloudIoT. Our PDAC improves the previous privacy-preserving distributed ABE systems in three aspects. The first introduces a new user's anonymity approach against the colluding untrusted (honest-but-curious) authorities. The second presents a novel policy-hiding mechanism that efficiently preserves the privacy of policy-forming attributes (metadata) against colluding parties. The third introduces an independent-authorities system for our privacy-preserving improvements, where an authority can join and leave the system without reinitializing other authorities. Moreover, our PDAC offloads the user's computations over the Cloud servers for efficiency enhancement. We prove the security of our PDAC through formal analysis. Then, we present empirical results on different classes of mobile devices, including a laptop and a smartphone.