An Efficient Ciphertext-Policy Decryptable Attribute-Based Keyword Search Scheme with Dynamic Attribute Support

Safeguarding data confidentiality and enforcing precise access regulation in cloud platforms continue to be major research concerns. Attribute-based encryption (ABE) offers a versatile framework for policy-driven control, whereas public key encryption with keyword search (PEKS) supports efficient querying of encrypted datasets. However, ABE lacks keyword search support, and PEKS offers limited control over access policies. To overcome these limitations, attribute-based keyword search (ABKS) schemes have been proposed, with recent advances such as ciphertext-policy decryptable ABKS (CP-DABKS) enabling secure channel-free keyword search. Nevertheless, the existing CP-DABKS schemes still face important challenges: the master public key grows linearly with the attribute universe, secure channels are often required to deliver trapdoors, and many designs remain vulnerable to keyword guessing attacks. This work introduces an efficient CP-DABKS scheme built upon a Type-3 pairing framework to directly overcome these limitations. The proposed design employs a commit-to-point mechanism that prevents linear key growth, eliminates the need for secure trapdoor transmission, and resists keyword guessing attacks. We implement and evaluate the proposed scheme using real-world data from the Enron Email dataset and demonstrate its practicality for secure and searchable cloud-based storage. We also discuss implementation considerations and outline directions for future enhancement of privacy-preserving searchable encryption systems.