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A Key-Policy Attribute-Based Temporary Keyword Search scheme for Secure Cloud Storage

A Key-Policy Attribute-Based Temporary Keyword Search scheme for Secure Cloud Storage


Temporary keyword search on confidential data in a cloud environment is the main focus of this research. The cloud providers are not fully trusted. So, it is necessary to outsource data in the encrypted form. In the attribute-based keyword search (ABKS) schemes, the authorized users can generate some search tokens and send them to the cloud for running the search operation. These search tokens can be used to extract all the ciphertexts which are produced at any time and contain the corresponding keyword. Since this may lead to some information leakage, it is more secure to propose a scheme in which the search tokens can only extract the ciphertexts generated in a specified time interval. To this end, in this paper, we introduce a new cryptographic primitive called key-policy attribute-based temporary keyword search (KPABTKS) which provide this property. To evaluate the security of our scheme, we formally prove that our proposed scheme achieves the keyword secrecy property and is secure against selectively chosen keyword attack (SCKA) both in the random oracle model and under the hardness of Decisional Bilinear Diffie-Hellman (DBDH) assumption. Furthermore, we show that the complexity of the encryption algorithm is linear with respect to the number of the involved attributes. Performance evaluation shows our scheme’s practicality.


• A data owner cannot obtain any information about the keywords which the data users intend to look for.

• The direct access of the cloud to the sensitive information of its users threatens their privacy.

• A trivial solution to address this problem is encrypting data before outsourcing it to the cloud. However, searching on the encrypted data is very difficult.


Today’s IaaS clouds allow dynamic scaling of VMs allocated to a user, according to real-time demand of the user. There are two types of scaling: horizontal scaling (scale-out) by allocating more VM instances to the user, and vertical scaling (scale-up) by boosting resources of VMs owned by the user. It has been a daunting issue how to efficiently allocate the resources on physical servers to meet the scaling demand of users on the go, which achieves the best server utilization and user utility. An accompanying critical challenge is how to effectively charge the incremental resources, such that the economic benefits of both the cloud provider and cloud users are guaranteed. There has been online auction design dealing with dynamic VM provisioning, where the resource bids are not related to each other, failing to handle VM scaling where later bids may rely on earlier bids of the same user. As the first in the literature, this paper designs an efficient, truthful online auction for resource provisioning and pricing in the practical cases of dynamic VM scaling, where: (i) users bid for customized VMs to use in future durations, and can bid again in the following time to increase resources, indicating both scale-up and scale-out options; (ii) the cloud provider packs the demanded VMs on heterogeneous servers for energy cost minimization on the go. We carefully design resource prices maintained for each type of resource on each server to achieve threshold-based online allocation and charging, as well as a novel competitive analysis technique based on sub modularity of the offline objective, to show a good competitive ratio is achieved. The efficacy of the online auction is validated through solid theoretical analysis and trace-driven simulations.


In this work , we propose a novel notion of Key-Policy Attribute-Based Temporary Keyword Search (KP-ABTKS). In KP-ABTKS schemes, the data owner generates a searchable ciphertext related to a keyword and the time of encrypting according to an intended access control policy, and outsources it to the cloud. After that, each authorized data user selects an arbitrary time interval and generates a search token for the intended keyword to find the ciphertext. Then, he/she sends the generated token to the cloud to run the search operation. By receiving the token, the cloud looks for the documents contain the intended keyword. The search result on a ciphertext is positive, if (i) the data user’s attributes satisfies the access control policy, (ii) the time interval of the search token encompasses the time of encrypting, and (iii) the search token and the ciphertext are related to the same keyword. To show that the proposed notion can be realized, we also propose a concrete instantiation for this new cryptographic primitive based on bilinear map.


Securing cloud storage is an important problem in cloud computing. We addressed this issue and introduced the notion of key-policy attribute-based temporary keyword search (KPABTKS). According to this notion, each data user can generate a search token which is valid only for a limited time interval. We proposed the first concrete construction for this new cryptographic primitive based on bilinear map. We formally showed that our scheme is provably secure in the random oracle model. The complexity of encryption algorithm of our proposal is linear with respect to the number of the involved attributes. In addition, the number of required pairing in the search algorithms is independent of the number of the intended time units specified in the search token and it is linear with respect to the number of attributes. Performance evaluation of our scheme in term of both computational cost and execution time shows the practical aspects of the proposed scheme.