Integrity Auditing with Attribute based ECMRSA Algorithm for Cloud Data Outsourcing

2020 ◽  
Author(s):  
Yogita ◽  
Neetesh Kumar Gupta
Keyword(s):  
Data Outsourcing ◽  
Cloud Data

scholarly journals An enhanced security tree to secure cloud data

2017 ◽  
Vol 7 (1.1) ◽  
pp. 64 ◽  
Author(s):  
S. Renu ◽  
S.H. Krishna Veni
Keyword(s):  
Data Storage ◽  
Binary Tree ◽  
Data Encryption ◽  
Third Party ◽  
Data Outsourcing ◽  
Cloud Data ◽  
Security Issues ◽  
Security Services ◽  
Computing Services ◽  
User Data

The Cloud computing services and security issues are growing exponentially with time. All the CSPs provide utmost security but the issues still exist. Number of technologies and methods are emerged and futile day by day. In order to overcome this situation, we have also proposed a data storage security system using a binary tree approach. Entire services of the binary tree are provided by a Trusted Third Party (TTP) .TTP is a government or reputed organization which facilitates to protect user data from unauthorized access and disclosure. The security services are designed and implemented by the TTP and are executed at the user side. Data classification, Data Encryption and Data Storage are the three vital stages of the security services. An automated file classifier classify unorganized files into four different categories such as Sensitive, Private, Protected and Public. Applied cryptographic techniques are used for data encryption. File splitting and multiple cloud storage techniques are used for data outsourcing which reduces security risks considerably. This technique offers  file protection even when the CSPs compromise. 

scholarly journals EMSRSE: Efficient Multi-Keyword Synonym Based Ranked Search Technique Over Outsourced Encrypted Cloud Data

2018 ◽  
Vol 7 (4.36) ◽  
pp. 736
Author(s):  
Veerraju Gampala ◽  
Sreelatha Malempati
Keyword(s):  
Data Privacy ◽  
Cloud Service ◽  
Search Tree ◽  
Maintenance Cost ◽  
Data Outsourcing ◽  
Sensitive Data ◽  
Cloud Data ◽  
Insertion And Deletion ◽  
Ease Of Access ◽  
Result Analysis

Recently, searching over encrypted cloud-data outsourcing has attracted the current researcher. Using cloud computing (CC), individuals and organizations are motivated to outsource their private and sensitive data onto the cloud service provider (CSP) due to less maintenance cost, great flexibility, and ease of access.  However, the data should be encrypted using encryption techniques such as DES and AES before uploading to the CSP in order to provide data privacy and protection, which obsolete plaintext searching techniques over encrypted cloud data. Thus, this article proposes an efficient multi-keyword synonym-based ranked searching technique over encrypted cloud data (EMSRSE), which supports dynamic insertion and deletion of documents. The main objectives of EMSRSE are 1. To build an index search tree in order to store encrypted index vectors of documents and 2. To achieve better searching efficiency, a searching technique over the encrypted index tree is proposed. An extensive research and empirical result analysis show that the proposed EMSRSE scheme achieves better efficiency in comparison with other existing methods.  

Study of Dynamic Multikeyword Text Search Techniques over Encrypted Data in Cloud

2017 ◽  
Vol 7 (8) ◽  
pp. 326
Author(s):  
Ankita Puri ◽  
Naveen Kumari
Keyword(s):  
Data Retrieval ◽  
Modern Technology ◽  
Inner Product ◽  
Data Outsourcing ◽  
Keyword Query ◽  
Cloud Data ◽  
Data Services ◽  
Cloud Server ◽  
Efficient Data ◽  
Ranked Search

Day by Day ,with the advancement of modern technology over cloud computing motivating the data owners to outsource their data to the cloud server like Amazon, Microsoft, Azure etc .With the help of data outsourcing ,the organization can provide reliable data services to their user without any management of the overhead concern. Suppose, a large number of users that are on cloud and large number of documents on cloud, Its important for the service provider to allow multi-keyword query and provided the result that meet efficient data retrieval needs. In this paper, for the first time, we define and solve the challenging problem of privacy preserving multi-keyword ranked search over encrypted cloud data (MRSE), and establish a set of strict privacy requirements for such a secure cloud data utilization system to become a reality. Among various multi-keyword semantics, we choose the efficient principle of “coordinate matching”, i.e., as many matches as possible, to capture the similarity between search query and data documents, and further use “inner product similarity” to quantitatively formalize such principle for similarity measurement.

scholarly journals Overview of current techniques in remote data auditing

2016 ◽  
Vol 1 (1) ◽  
pp. 145-158 ◽  
Author(s):  
Hualong Wu ◽  
Bo Zhao
Keyword(s):  
Data Storage ◽  
Erasure Coding ◽  
Network Access ◽  
Data Outsourcing ◽  
Local Data ◽  
Cloud Data ◽  
Resource Pooling ◽  
Outsourced Data ◽  
Data Auditing ◽  
Remote Data

AbstractThe emergence of cloud computing brings the infinite imagination space, both in individual and organizations, due to its unprecedented advantages in the IT history: on-demand self-service, ubiquitous network access, location independent resource pooling, rapid resource elasticity, usage-based pricing and transference of risk. Many of the individuals or organizations ease the pressure on their local data storage, and mitigate the maintenance overhead of local data storage by using outsource data to cloud. However, the data outsourcing is not absolutely safe in the cloud. In order to enhance the users’ confidence of the integrity of their outsource data in the cloud. To promote the rapid deployment of cloud data storage service and regain security assurances with outsourced data dependability, many scholars tend to design the Remote Data Auditing (RDA) technique as a new concept to enable public auditability for the outsourced data in the cloud. The RDA is a useful technique to ensure the correctness of the data outsourced to cloud servers. This paper presents a comprehensive survey on techniques of remote data auditing in cloud server. Recently, more and more remote auditing approaches are categorized into the three different classes, that is, replication-based, erasure coding-based, and network coding-based to present a taxonomy. This paper also aims to the explore major issues.

scholarly journals Study of Dynamic Multikeyword Text Search Techniques over Encrypted Data in Cloud

2017 ◽  
Vol 7 (7) ◽  
pp. 313
Author(s):  
Ankita Puri ◽  
Naveen Kumari
Keyword(s):  
Data Retrieval ◽  
Modern Technology ◽  
Inner Product ◽  
Data Outsourcing ◽  
Keyword Query ◽  
Cloud Data ◽  
Data Services ◽  
Cloud Server ◽  
Efficient Data ◽  
Ranked Search

Day by Day ,with the advancement of modern technology over cloud computing motivating the data owners to outsource their data to the cloud server like Amazon, Microsoft, Azure etc .With the help of data outsourcing ,the organization can provide reliable data services to their user without any management of the overhead concern. Suppose, a large number of users that are on cloud and large number of documents on cloud, Its important for the service provider to allow multi-keyword query and provided the result that meet efficient data retrieval needs. In this paper, for the first time, we define and solve the challenging problem of privacy preserving multi-keyword ranked search over encrypted cloud data (MRSE), and establish a set of strict privacy requirements for such a secure cloud data utilization system to become a reality. Among various multi-keyword semantics, we choose the efficient principle of “coordinate matching”, i.e., as many matches as possible, to capture the similarity between search query and data documents, and further use “inner product similarity” to quantitatively formalize such principle for similarity measurement.

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