7 research outputs found

    Using Attribute-Based Access Control, Efficient Data Access in the Cloud with Authorized Search

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    The security and privacy issues regarding outsourcing data have risen significantly as cloud computing has grown in demand. Consequently, since data management has been delegated to an untrusted cloud server in the data outsourcing phase, data access control has been identified as a major problem in cloud storage systems. To overcome this problem, in this paper, the access control of cloud storage using an Attribute-Based Access Control (ABAC) approach is utilized. First, the data must be stored in the cloud and security must be strong for the user to access the data. This model takes into consideration some of the attributes of the cloud data stored in the authentication process that the database uses to maintain data around the recorded collections with the user\u27s saved keys. The clusters have registry message permission codes, usernames, and group names, each with its own set of benefits. In advance, the data should be encrypted and transferred to the service provider as it establishes that the data is still secure. But in some cases, the supplier\u27s security measures are disrupting. This result analysis the various parameters such as encryption time, decryption time, key generation time, and also time consumption. In cloud storage, the access control may verify the various existing method such as Ciphertext Policy Attribute-Based Encryption (CP-ABE) and Nth Truncated Ring Units (NTRU). The encryption time is 15% decreased by NTRU and 31% reduced by CP-ABE. The decryption time of the proposed method is 7.64% and 14% reduced by the existing method

    Efficient enhanced keyword search for encrypted document in cloud

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    A sensitive public-key searchable encryption system in the prime-order groups, which lets keyword search policies to be uttered in conjunctive, disjunctive or any monotonic Boolean formulas and realizes momentous act enhancement over existing schemes. We legally express its sanctuary, and verify that it is selectively sheltered in the standard model. Correspondingly, we instrument the wished-for outline using a hasty prototyping tool so-called Charm and conduct more than a few experiments to estimate it show. The results determine that our scheme is plentiful more proficient than the ones assembled over the composite-order groups. Keyword research is one of the most imperative, valuable, and high return activities in the search marketing field. Position for the right keywords can make or interruption your website

    Privacy-preserving data search with fine-grained dynamic search right management in fog-assisted Internet of Things

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    This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Fog computing, as an assisted method for cloud computing, collects Internet of Things (IoT) data to multiple fog nodes on the edge of IoT and outsources them to the cloud for data search, and it reduces the computation cost on IoT nodes and provides fine-grained search right management. However, to provide privacy-preserving IoT data search, the existing searchable encryptions are very inefficient as the computation cost is too high for the resource-constrained IoT ends. Moreover, to provide dynamic search right management, the users need to be online all the time in the existing schemes, which is impractical. In this paper, we first present a new fog-assisted privacy-preserving IoT data search framework, where the data from each IoT device is collected by a fog node, stored in a determined document and outsourced to the cloud, the users search the data through the fog nodes, and the fine-grained search right management is maintained at document level. Under this framework, two searchable encryption schemes are proposed, i.e., Credible Fog Nodes assisted Searchable Encryption (CFN-SE) and Semi-trusted Fog Nodes assisted Searchable Encryption (STFN-SE). In CFN-SE scheme, the indexes and trapdoors are generated by the fog nodes, which greatly reduce the computation costs at the IoT devices and user ends, and fog nodes are used to support offline users’ key update. In STFN-SE scheme, the semi-trusted fog nodes are used to provide storage of encrypted key update information to assist offline users’ search right update. In both schemes, no re-encryption of the keywords is needed in search right updates. The performance evaluations of our schemes demonstrate the feasibility and high efficiency of our system.National Key Research and Development ProgramNational Natural Science Foundation of ChinaSichuan Provincial Major Frontier IssuesState Key Laboratory of Integrated Services Networks, Xidian Universit

    E-Tenon: An efficient privacy-preserving secure open data sharing scheme for EHR system

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    The transition from paper-based information to Electronic-Health-Records (EHRs) has driven various advancements in the modern healthcare industry. In many cases, patients need to share their EHR with healthcare professionals. Given the sensitive and security-critical nature of EHRs, it is essential to consider the security and privacy issues of storing and sharing EHR. However, existing security solutions excessively encrypt the whole database, thus requiring the entire database to be decrypted for each access request, which is time-consuming. On the other hand, the use of EHR for medical research (e.g., development of precision medicine and diagnostics techniques) and optimisation of practices in healthcare organisations require the EHR to be analysed. To achieve that, they should be easily accessible without compromising the patient’s privacy. In this paper, we propose an efficient technique called E-Tenon that not only securely keeps all EHR publicly accessible but also provides the desired security features. To the best of our knowledge, this is the first work in which an Open Database is used for protecting EHR. The proposed E-Tenon empowers patients to securely share their EHR under their own multi-level, fine-grained access policies. Analyses show that our system outperforms existing solutions in terms of computational complexity

    Hybrid Publicly Verifiable Computation

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    Publicly Verifiable Outsourced Computation (PVC) allows weak devices to delegate computations to more powerful servers, and to verify the correctness of results. Delegation and verification rely only on public parameters, and thus PVC lends itself to large multi-user systems where entities need not be registered. In such settings, individual user requirements may be diverse and cannot be realised with current PVC solutions. In this paper, we introduce Hybrid PVC (HPVC) which, with a single setup stage, provides a flexible solution to outsourced computation supporting multiple modes: (i) standard PVC, (ii) PVC with cryptographically enforced access control policies restricting the servers that may perform a given computation, and (iii) a reversed model of PVC which we call Verifiable Delegable Computation (VDC) where data is held remotely by servers. Entities may dynamically play the role of delegators or servers as required

    Authorized Keyword Search on Encrypted Data

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