A survey paper of data access privilege scheme in cloud storage server for user privacy problem

Storing the data in cloud helps in satisfying the demand of data access at anyplace, anytime. In cloud storage, users authenticate whether the data has been stored to the cloud storage server correctly. In order to enhance the storage provision, an Effectual Homomorphic Tag based Block for Dynamic Provable Data Possession (EHTB-DPDP) framework has been designed. This framework checks for the data integrity in the cloud storage server. The existing PDP, DPDP schemes were analyzed and the drawbacks encountered in those systems have been reframed using the proposed methodology. The major benefit of the proposed EHTB-DPDP is that it offers an effectual dynamic provable data possession and data integrity. This scheme spotlights on the integrity of the remote data by reducing data storage space, so that users can retrieve data efficiently. This security enhancement is achieved by the block tagging methodology. In addition, converting the variable block size to the fixed block size using hash function is also investigated. The feasibility of the scheme is proved by aanlyzing the security and the performance

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Universal Keyword Classifier on Public Key Based Encrypted Multikeyword Fuzzy Search in Public Cloud

The Scientific World JOURNAL ◽

10.1155/2015/706102 ◽

2015 ◽

Vol 2015 ◽

pp. 1-17

Author(s):

Shyamala Devi Munisamy ◽

Arun Chokkalingam

Keyword(s):

Cloud Storage ◽

Data Access ◽

Cloud Services ◽

Third Party ◽

Public Cloud ◽

Data Utilization ◽

Storage Server ◽

Fuzzy Search ◽

Private Data ◽

Fuzzy Searching

Cloud computing has pioneered the emerging world by manifesting itself as a service through internet and facilitates third party infrastructure and applications. While customers have no visibility on how their data is stored on service provider’s premises, it offers greater benefits in lowering infrastructure costs and delivering more flexibility and simplicity in managing private data. The opportunity to use cloud services on pay-per-use basis provides comfort for private data owners in managing costs and data. With the pervasive usage of internet, the focus has now shifted towards effective data utilization on the cloud without compromising security concerns. In the pursuit of increasing data utilization on public cloud storage, the key is to make effective data access through several fuzzy searching techniques. In this paper, we have discussed the existing fuzzy searching techniques and focused on reducing the searching time on the cloud storage server for effective data utilization. Our proposedAsymmetric Classifier Multikeyword Fuzzy Searchmethod provides classifier search server that creates universal keyword classifier for the multiple keyword request which greatly reduces the searching time by learning the search path pattern for all the keywords in the fuzzy keyword set. The objective of using BTree fuzzy searchable index is to resolve typos and representation inconsistencies and also to facilitate effective data utilization.

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Digital Forensics Study of a Cloud Storage Client: A Dropbox Artifact Analysis

CommIT (Communication and Information Technology) Journal ◽

10.21512/commit.v13i2.5781 ◽

2019 ◽

Vol 13 (2) ◽

Author(s):

Gandeva Bayu Satrya

Keyword(s):

Privacy Protection ◽

Cloud Storage ◽

Digital Forensics ◽

Rapid Development ◽

User Privacy ◽

Criminal Cases ◽

Storage Server ◽

Artifact Analysis ◽

Multiple Devices ◽

Client Side

The rapid development of cloud storage technology paired with the prevalence of smartphone usage presents wide-ranging challenges for digital forensics practitioners. Data are more easily uploaded and shared between multiple devices and across multiple platforms. So, it has increased the opportunities for criminality. Criminality undertaken in cloud computing can be directly seen on logs stored on the cloud storage server, which records user activity. However, because of user privacy protection, these logs cannot be easily used as evidence in court. This issue emphasizes the need for a reliable means of identifying, acquiring, and preserving evidential data from the client-side. This study identifies the data artifacts of a user accessing Dropbox via smartphone (Android Lollipop and Android Nougat). The data are from performing several common activities such as installing, signing up, uploading, downloading, sharing, and others. About 14 artifacts are identified by documenting the Dropbox client database changing contents as these activities are carried out. This study increases knowledge of the artifacts that are leftover by Dropbox client on Android smartphones. The results propose that these methods can be used by digital forensics investigators in carrying out investigations and cyberlaw practitioners as guidance in criminal cases.

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Secure Data Access and Sharing Scheme for Cloud Storage

Wireless Personal Communications ◽

10.1007/s11277-016-3742-6 ◽

2016 ◽

Vol 96 (4) ◽

pp. 5295-5314 ◽

Cited By ~ 8

Author(s):

Xiong Li ◽

Saru Kumari ◽

Jian Shen ◽

Fan Wu ◽

Caisen Chen ◽

...

Keyword(s):

Cloud Storage ◽

Data Access ◽

Sharing Scheme ◽

Secure Data

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Device-Based Security to Improve User Privacy in the Internet of Things †

Sensors ◽

10.3390/s18082664 ◽

2018 ◽

Vol 18 (8) ◽

pp. 2664 ◽

Cited By ~ 4

Author(s):

Luis Belem Pacheco ◽

Eduardo Pelinson Alchieri ◽

Priscila Mendez Barreto

Keyword(s):

Cloud Computing ◽

Internet Of Things ◽

Single Point ◽

Data Access ◽

Cloud Services ◽

Sensitive Information ◽

User Privacy ◽

Privacy And Security ◽

Iot Devices ◽

And Control

The use of Internet of Things (IoT) is rapidly growing and a huge amount of data is being generated by IoT devices. Cloud computing is a natural candidate to handle this data since it has enough power and capacity to process, store and control data access. Moreover, this approach brings several benefits to the IoT, such as the aggregation of all IoT data in a common place and the use of cloud services to consume this data and provide useful applications. However, enforcing user privacy when sending sensitive information to the cloud is a challenge. This work presents and evaluates an architecture to provide privacy in the integration of IoT and cloud computing. The proposed architecture, called PROTeCt—Privacy aRquitecture for integratiOn of internet of Things and Cloud computing, improves user privacy by implementing privacy enforcement at the IoT devices instead of at the gateway, as is usually done. Consequently, the proposed approach improves both system security and fault tolerance, since it removes the single point of failure (gateway). The proposed architecture is evaluated through an analytical analysis and simulations with severely constrained devices, where delay and energy consumption are evaluated and compared to other architectures. The obtained results show the practical feasibility of the proposed solutions and demonstrate that the overheads introduced in the IoT devices are worthwhile considering the increased level of privacy and security.

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Study of privacy-preserving framework for cloud storage

Computer Science and Information Systems ◽

10.2298/csis100327029r ◽

2011 ◽

Vol 8 (3) ◽

pp. 801-819 ◽

Cited By ~ 12

Author(s):

Huang Ruwei ◽

Gui Xiaolin ◽

Yu Si ◽

Zhuang Wei

Keyword(s):

Data Storage ◽

Cloud Storage ◽

Security Analysis ◽

Bloom Filter ◽

Data Access ◽

Data Retrieval ◽

Privacy Preserving ◽

Index Structure ◽

Structure Generation ◽

Access Right

In order to implement privacy-preserving, efficient and secure data storage and access environment of cloud storage, the following problems must be considered: data index structure, generation and management of keys, data retrieval, treatments of change of users? access right and dynamic operations on data, and interactions among participants. To solve those problems, the interactive protocol among participants is introduced, an extirpation-based key derivation algorithm (EKDA) is designed to manage the keys, a double hashed and weighted Bloom Filter (DWBF) is proposed to retrieve the encrypted keywords, which are combined with lazy revocation, multi-tree structure, asymmetric and symmetric encryptions, which form a privacypreserving, efficient and secure framework for cloud storage. The experiment and security analysis show that EKDA can reduce the communication and storage overheads efficiently, DWBF supports ciphertext retrieval and can reduce communication, storage and computation overhead as well, and the proposed framework is privacy preserving while supporting data access efficiently.

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