Attribute-Based Encryption With Verifiable Outsourced Decryption

By Junzuo Lai, Robert Huijie Deng, Chaowen Guan, Jian Weng. IEEE Transactions on Information Forensics and Security, 2013

427 citations recorded by the source corpus.

Attribute-based encryption (ABE) is a public-key-based one-to-many encryption that allows users to encrypt and decrypt data based on user attributes. A promising application of ABE is flexible access control of encrypted data stored in the cloud, using access polices and ascribed attributes associated with private keys and ciphertexts. One of the main efficiency drawbacks of the existing ABE schemes is that decryption involves expensive pairing operations and the number of such operations grows with the complexity of the access policy. Recently, Green et al. proposed an ABE system with outsourced decryption that largely eliminates the decryption overhead for users. In such a system, a user provides an untrusted server, say a cloud service provider, with a transformation key that allows the cloud to translate any ABE ciphertext satisfied by that user's attributes or access policy into a simple ciphertext, and it only incurs a small computational overhead for the user to recover the plaintext from the transformed ciphertext. Security of an ABE system with outsourced decryption ensures that an adversary (including a malicious cloud) will not be able to learn anything about the encrypted message; however, it does not guarantee the correctness of the transformation done by the cloud. In this paper, we consider a new requirement of ABE with outsourced decryption: verifiability. Informally, verifiability guarantees that a user can efficiently check if the transformation is done correctly. We give the formal model of ABE with verifiable outsourced decryption and propose a concrete scheme. We prove that our new scheme is both secure and verifiable, without relying on random oracles. Finally, we show an implementation of our scheme and result of performance measurements, which indicates a significant reduction on computing resources imposed on users.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/ca9927176c857d1fd8a711887d0964dddaec735d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Xinyi Huang
2. Xiaofeng Chen
3. Yang Xiang
4. Lei Yang
5. Xiaonan Lin
6. Jin Li
7. Yicheng Zhang
8. Jinguang Han

In Computational Theory and Mathematics

1. Xinyi Huang
2. Xiaofeng Chen
3. Yang Xiang
4. Lei Yang
5. Jin Li
6. Jingwei Li

Citations in the corpus

• KSF-OABE: Outsourced Attribute-Based Encryption with Keyword Search Function for Cloud Storage (2017, background): “In order to solve the problem, some ABE schemes [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27] have been proposed to outsource the”
• Security and Privacy in the Internet of Things (2017, methodology): “implemented a verifiable outsourced ABE approach by attaching an additional encrypted random message to the real message and computing the digest of the two messages together [99].”
• Securely Outsourcing Attribute-Based Encryption with Checkability (2014, methodology): “Additionally, we consider a security and functionality enhanced construction enabling checkability on returned results from CSPs. Recently Lai et al. [28] proposed a concrete construction for ABE with verifiable decryption, which achieves both security and verifiability without random oracles.”