Hidden policy ciphertext-policy attribute-based encryption with keyword search against keyword guessing attack

2016 ◽  
Vol 60 (5) ◽  
Author(s):  
Shuo Qiu ◽  
Jiqiang Liu ◽  
Yanfeng Shi ◽  
Rui Zhang
Author(s):  
Fei Meng ◽  
Leixiao Cheng ◽  
Mingqiang Wang

AbstractCountless data generated in Smart city may contain private and sensitive information and should be protected from unauthorized users. The data can be encrypted by Attribute-based encryption (CP-ABE), which allows encrypter to specify access policies in the ciphertext. But, traditional CP-ABE schemes are limited because of two shortages: the access policy is public i.e., privacy exposed; the decryption time is linear with the complexity of policy, i.e., huge computational overheads. In this work, we introduce a novel method to protect the privacy of CP-ABE scheme by keyword search (KS) techniques. In detail, we define a new security model called chosen sensitive policy security: two access policies embedded in the ciphertext, one is public and the other is sensitive and hidden. If user's attributes don't satisfy the public policy, he/she cannot get any information (attribute name and its values) of the hidden one. Previous CP-ABE schemes with hidden policy only work on the “AND-gate” access structure or their ciphertext size or decryption time maybe super-polynomial. Our scheme is more expressive and compact. Since, IoT devices spread all over the smart city, so the computational overhead of encryption and decryption can be shifted to third parties. Therefore, our scheme is more applicable to resource-constrained users. We prove our scheme to be selective secure under the decisional bilinear Diffie-Hellman (DBDH) assumption.


2021 ◽  
Vol 74 ◽  
pp. 103471
Author(s):  
Jiguo Li ◽  
Min Wang ◽  
Yang Lu ◽  
Yichen Zhang ◽  
Huaqun Wang

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Mingsheng Cao ◽  
Luhan Wang ◽  
Zhiguang Qin ◽  
Chunwei Lou

The wireless body area networks (WBANs) have emerged as a highly promising technology that allows patients’ demographics to be collected by tiny wearable and implantable sensors. These data can be used to analyze and diagnose to improve the healthcare quality of patients. However, security and privacy preserving of the collected data is a major challenge on resource-limited WBANs devices and the urgent need for fine-grained search and lightweight access. To resolve these issues, in this paper, we propose a lightweight fine-grained search over encrypted data in WBANs by employing ciphertext policy attribute based encryption and searchable encryption technologies, of which the proposed scheme can provide resource-constraint end users with fine-grained keyword search and lightweight access simultaneously. We also formally define its security and prove that it is secure against both chosen plaintext attack and chosen keyword attack. Finally, we make a performance evaluation to demonstrate that our scheme is much more efficient and practical than the other related schemes, which makes the scheme more suitable for the real-world applications.


2019 ◽  
Vol 63 (8) ◽  
pp. 1203-1215 ◽  
Author(s):  
Yang Chen ◽  
Wenmin Li ◽  
Fei Gao ◽  
Kaitai Liang ◽  
Hua Zhang ◽  
...  

Abstract To date cloud computing may provide considerable storage and computational power for cloud-based applications to support cryptographic operations. Due to this benefit, attribute-based keyword search (ABKS) is able to be implemented in cloud context in order to protect the search privacy of data owner/user. ABKS is a cryptographic primitive that can provide secure search services for users but also realize fine-grained access control over data. However, there have been two potential problems that prevent the scalability of ABKS applications. First of all, most of the existing ABKS schemes suffer from the outside keyword guessing attack (KGA). Second, match privacy should be considered while supporting multi-keyword search. In this paper, we design an efficient method to combine the keyword search process in ABKS with inner product encryption and deploy several proposed techniques to ensure the flexibility of retrieval mode, the security and efficiency of our scheme. We later put forward an attribute-based conjunctive keyword search scheme against outside KGA to solve the aforementioned problems. We provide security notions for two types of adversaries and our construction is proved secure against chosen keyword attack and outside KGA. Finally, all-side simulation with real-world data set is implemented for the proposed scheme, and the results of the simulation show that our scheme achieves stronger security without yielding significant cost of storage and computation.


2019 ◽  
Vol 30 (02) ◽  
pp. 255-273 ◽  
Author(s):  
Min-Shiang Hwang ◽  
Cheng-Chi Lee ◽  
Shih-Ting Hsu

The idea of public key encryption with keyword search (PEKS), proposed by Boneh et al., enables one to send a trapdoor containing a encrypted keyword to query data without revealing the keyword. In Boneh et al.’s design, the trapdoor has to be transferred through a secure channel, which is both costly and inefficient. Baek et al. then proposed an efficient secure channel free public key encryption scheme with keyword search (SCF-PEKS). After that, vast amounts of research have focused on the protection against the off-line keyword guessing attack (OKGA) by enhancing the model. However, most of the PEKS/SCF-PEKS schemes developed so far are constructed by applying bilinear pairing and are susceptible to off-line keyword guessing attacks. In this paper, we propose a new SCF-PEKS scheme based on the ElGamal cryptosystem. The proposed scheme is not only secure against off-line keyword guessing attacks but also improves the efficiency.


Sign in / Sign up

Export Citation Format

Share Document