Abstract
With the widespread application of the Internet of Things (IoT) technology, it is expected to become a new data management model. But IoT devices have limited resource storage and computing power, they are highly vulnerable to hackers and leak sensitive information to third parties. The traditional attribute-based searchable encryption schemes usually require an intelligent terminal to perform complex calculations while accessing data, therefore IoT devices may not be able to withstand excessive calculation burden. In this paper, we present a keyword searchable attribute-based encryption scheme with equality test (KS-ABESwET) in the IoT by combining the notions of attribute-based searchable encryption (ABSE) with equality test. The proposed scheme adopts a keyword search algorithm based on the inverted index and equality test mechanism. If the keyword token match index is successful, the cloud server sends all ciphertexts that meet the conditions to the data user. Then, data user classifies the ciphertexts by equality test mechanism, which is executed by the authorized cloud server to determine whether the two ciphertexts encrypted by different access policies contain the same plaintext without decrypting. In this way, data user does not need to decrypt all ciphertexts, which decreases storage resource consumption of IoT devices and simplifies the complex operations generated by the traditional ABSE schemes. Using outsourcing technology, most calculations in the scheme are outsourced to the server, and IoT devices only perform a few calculations, which reduces greatly the computing and storage burden. Based on the decisional $q-1$ assumption and decisional Diffie-Hellman (DDH) assumption, the proposed scheme proves that has chosen-plaintext security and chosen-keyword security. Moreover, through comparative analysis and experimental simulation, our scheme is effective and suitable for IoT environment.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.