Multiauthority KP-ABE access model with elliptic curve cryptography

Abstract

The rapid and expansive integration of Internet of Things (IoT) environments across various industrial sectors has led to an unprecedented surge in data generation and management. This exponential growth in data underscores the critical necessity for robust data security methodologies that can effectively safeguard the confidentiality and integrity of information without imposing undue computational burdens. In response to this challenge, numerous studies have sought to leverage Attribute-Based Encryption (ABE) as a means to enable fine-grained access control. Among the ABE variants, Ciphertext Policy ABE (CP-ABE) and bilinear pairings have emerged as popular choices to construct security schemes that strike a balance between robust protection and computational efficiency. Despite the advancements achieved through CP-ABE and bilinear pairings, a prevalent concern arises in the utilization of Linear Secret Sharing Scheme (LSSS) access policies. LSSS policies, while providing a flexible and expressive way to define access controls, can significantly impact the execution time of encryption methods. This study recognizes the importance of addressing this challenge and explores the potential of employing a Key Policy Attribute-Based Encryption (KP-ABE) approach. The primary objective is to mitigate the computational overhead associated with encryption methods, thereby enhancing the efficiency of data security measures within IoT environments. Furthermore, this research delves into the incorporation of Elliptic Curve Cryptography (ECC) to generate cryptographic keys. ECC, known for its strong security properties and computational efficiency, is considered a promising approach to bolster data security while concurrently minimizing computational overhead. By integrating KP-ABE with ECC, this study aims to offer a comprehensive solution that ensures robust security measures within the intricate landscape of IoT environments. Through detailed analysis and empirical investigation, the research endeavors to contribute valuable insights to the ongoing discourse on securing IoT data in a manner that aligns with the dual imperatives of security and computational efficiency.