Container Based Cloud Data Accessibility Improvement Method Using REST-API Based Third Party Transmission

2021 ◽  
Vol 46 (10) ◽  
pp. 1709-1718
Author(s):  
Sang-kwon Lee ◽  
Woo-jin Seok ◽  
Jung-hoon Moon ◽  
Won-taek Hong ◽  
Ki-hyeon Kim ◽  
...  
Keyword(s):  
Third Party ◽  
Data Accessibility ◽  
Cloud Data ◽  
Improvement Method ◽  
Rest Api

A Group Collaboratable Proof of Retrievability Scheme for Cloud Data Storage

2014 ◽  
Vol 13 (7) ◽  
pp. 4625-4632
Author(s):  
Jyh-Shyan Lin ◽  
Kuo-Hsiung Liao ◽  
Chao-Hsing Hsu
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Cloud Service ◽  
Third Party ◽  
Group Collaboration ◽  
Cloud Data ◽  
Cloud Data Storage ◽  
Important Trend ◽  
Data Update ◽  
Proof Of Retrievability

Cloud computing and cloud data storage have become important applications on the Internet. An important trend in cloud computing and cloud data storage is group collaboration since it is a great inducement for an entity to use a cloud service, especially for an international enterprise. In this paper we propose a cloud data storage scheme with some protocols to support group collaboration. A group of users can operate on a set of data collaboratively with dynamic data update supported. Every member of the group can access, update and verify the data independently. The verification can also be authorized to a third-party auditor for convenience.

scholarly journals Securing Cloud Data using RSA Algorithm

2018 ◽  
Vol 6 (4) ◽  
pp. 96
Author(s):  
Md Equebal Hussain ◽  
Mohammad Rashid Hussain
Keyword(s):  
Storage Capacity ◽  
Internet Security ◽  
Third Party ◽  
Combined Method ◽  
Cloud Data ◽  
Security Issues ◽  
Rsa Algorithm ◽  
Private Key ◽  
Important Concern ◽  
Encryption Algorithms

security is one of the most important concern on cloud computing therefore institutions are hesitating to host their data over cloud. Not all data can be afforded to move on the cloud (example accounts data). The main purpose of moving data over cloud is to reduce cost (infrastructure and maintenance), faster performance, easy upgrade, storage capacity but at the same time security is major concern because cloud is not private but maintained by third party over the internet, security issues like privacy, confidentiality, authorization (what you are allowed to do), authentication (who you are) and accounting (what you actually do) will be encountered. Variety of encryption algorithms required for higher level of security. In this paper we try to provide solution for better security by proposing a combined method of key exchange algorithm with encryption technique. Data stored in cloud can be protected from hackers using proposed solution because even if transmitted key is hacked of no use without user’s private key.

scholarly journals Comparable Encryption Scheme over Encrypted Cloud Data in Internet of Everything

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Qian Meng ◽  
Jianfeng Ma ◽  
Kefei Chen ◽  
Yinbin Miao ◽  
Tengfei Yang
Keyword(s):  
Model Performance ◽  
Data Integrity ◽  
Cloud Service ◽  
Third Party ◽  
Encryption Scheme ◽  
Cloud Data ◽  
Practical Applications ◽  
Internet Of Everything ◽  
Window Method ◽  
Comparable Encryption

User authentication has been widely deployed to prevent unauthorized access in the new era of Internet of Everything (IOE). When user passes the legal authentication, he/she can do series of operations in database. We mainly concern issues of data security and comparable queries over ciphertexts in IOE. In traditional database, a Short Comparable Encryption (SCE) scheme has been widely used by authorized users to conduct comparable queries over ciphertexts, but existing SCE schemes still incur high storage and computational overhead as well as economic burden. In this paper, we first propose a basic Short Comparable Encryption scheme based on sliding window method (SCESW), which can significantly reduce computational and storage burden as well as enhance work efficiency. Unfortunately, as the cloud service provider is a semitrusted third party, public auditing mechanism needs to be furnished to protect data integrity. To further protect data integrity and reduce management overhead, we present an enhanced SCESW scheme based on position-aware Merkle tree, namely, PT-SCESW. Security analysis proves that PT-SCESW and SCESW schemes can guarantee completeness and weak indistinguishability in standard model. Performance evaluation indicates that PT-SCESW scheme is efficient and feasible in practical applications, especially for smarter and smaller computing devices in IOE.

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 Bio::DB::NextProt: A Perl Module for neXtProt Database Information Retrieval

2014 ◽  
Author(s):  
Felipe V Leprevost
Keyword(s):  
Object Oriented ◽  
Third Party ◽  
Reference Database ◽  
Perl Module ◽  
Comprehensive Knowledge ◽  
Knowledge Platform ◽  
Structured Information ◽  
Rest Api ◽  
Human Proteome Project ◽  
Fast Dynamic

The neXtProt database is a comprehensive knowledge platform recently adopted by the Chromosome-centric Human Proteome Project as the main reference database. The primary goal of the project is to identify and catalog every human protein encoded in the human genome. For such, computational approaches have an important role as data analysis and dedicated software are indispensable. Here we describe Bio::DB::NextProt, a Perl module that provides an object-oriented access to the neXtProt REST Web services, enabling the programatically retrieval of structured information. The Bio::DB::NextProt module presents a new way to interact and download information from the neXtProt database. Every parameter available through REST API is covered by the module allowing a fast, dynamic and ready-to-use alternative for those who need to access neXtProt data. Bio::DB::NextProt is an easy-to-use module that provides automatically retrieval of data, ready to be integrated into third-party software or to be used by other programmers on the fly. The module is freely available from from CPAN (metacpan.org/release/Bio-DB-NextProt) and GitHub (github.com/Leprevost/Bio-DB-NextProt) and is released under the perl\_5 license.

scholarly journals Enhanced Integrity Checking for Preserve Data Owner and User Level Privacy Using Dual Cryptography Approach

2019 ◽  
pp. 138-146
Author(s):  
Poovizhi. M ◽  
Raja. G
Keyword(s):  
Data Storage ◽  
Data Privacy ◽  
Capital Expenditure ◽  
Data Access ◽  
Third Party ◽  
Configurable Computing ◽  
Local Data ◽  
Cloud Data ◽  
On Demand ◽  
Integrity Checking

Using Cloud Storage, users can tenuously store their data and enjoy the on-demand great quality applications and facilities from a shared pool of configurable computing resources, without the problem of local data storage and maintenance. However, the fact that users no longer have physical possession of the outsourced data makes the data integrity protection in Cloud Computing a formidable task, especially for users with constrained dividing resources. From users’ perspective, including both individuals and IT systems, storing data remotely into the cloud in a flexible on-demand manner brings tempting benefits: relief of the burden for storage management, universal data access with independent geographical locations, and avoidance of capital expenditure on hardware, software, and personnel maintenances, etc. To securely introduce an effective Sanitizer and third party auditor (TPA), the following two fundamental requirements have to be met: 1) TPA should be able to capably audit the cloud data storage without demanding the local copy of data, and introduce no additional on-line burden to the cloud user; 2) The third party auditing process should take in no new vulnerabilities towards user data privacy. In this project, utilize and uniquely combine the public auditing protocols with double encryption approach to achieve the privacy-preserving public cloud data auditing system, which meets all integrity checking without any leakage of data. To support efficient handling of multiple auditing tasks, we further explore the technique of online signature to extend our main result into a multi-user setting, where TPA can perform multiple auditing tasks simultaneously. We can implement double encryption algorithm to encrypt the data twice and stored cloud server in Electronic Health Record applications.

Privacy Preserving and Efficient Outsourcing Algorithm to Public Cloud

2021 ◽  
pp. 857-878
Author(s):  
Malay Kumar ◽  
Manu Vardhan
Keyword(s):  
Data Privacy ◽  
Classification Systems ◽  
Third Party ◽  
Cloud Data ◽  
Computing Services ◽  
Cloud Server ◽  
Cloud Computing Services ◽  
Cloud Data Centers ◽  
Outsourcing Algorithm ◽  
Direct Implementation

The growth of the cloud computing services and its proliferation in business and academia has triggered enormous opportunities for computation in third-party data management settings. This computing model allows the client to outsource their large computations to cloud data centers, where the cloud server conducts the computation on their behalf. But data privacy and computational integrity are the biggest concern for the client. In this article, the authors attempt to present an algorithm for secure outsourcing of a covariance matrix, which is the basic building block for many automatic classification systems. The algorithm first performs some efficient transformation to protect the privacy and verify the computed result produced by the cloud server. Further, an analytical and experimental analysis shows that the algorithm is simultaneously meeting the design goals of privacy, verifiability and efficiency. Also, found that the proposed algorithm is about 7.8276 times more efficient than the direct implementation.

Byzantine Fault-Tolerant Architecture in Cloud Data Management

2016 ◽  
Vol 7 (3) ◽  
pp. 86-98 ◽  
Author(s):  
Mohammed A. AlZain ◽  
Alice S. Li ◽  
Ben Soh ◽  
Mehedi Masud
Keyword(s):  
Cloud Computing ◽  
Data Management ◽  
Service Provider ◽  
Fault Tolerant ◽  
Academic Research ◽  
Third Party ◽  
Cloud Data ◽  
Byzantine Faults ◽  
Byzantine Fault ◽  
Cloud Data Management

One of the main challenges in cloud computing is to build a healthy and efficient storage for securely managing and preserving data. This means a cloud service provider needs to make sure that its clients' outsourced data are stored securely and, data queries and retrievals are executed correctly and privately. On the other hand, it may also mean businesses are willing to outsource their data to a third party only if they trust their data are not accessible and visible to the service provider and other non-authorized parties. However, one of the major obstacles faced here for ensuring data reliability and security is Byzantine faults. While Byzantine fault tolerance (BFT) has received growing attention from the academic research community, the research done is generally from the distributed computing point of view, and hence finds little practical use in cloud computing. To that end, the focus of this paper is to discuss how these faults can be tolerated with the authors' proposed conceptualization of Byzantine data faults and fault-tolerant architecture in cloud data management.

Privacy Preserving and Efficient Outsourcing Algorithm to Public Cloud

2018 ◽  
Vol 12 (2) ◽  
pp. 1-25 ◽  
Author(s):  
Malay Kumar ◽  
Manu Vardhan
Keyword(s):  
Data Privacy ◽  
Classification Systems ◽  
Third Party ◽  
Cloud Data ◽  
Computing Model ◽  
Computing Services ◽  
Cloud Server ◽  
Cloud Computing Services ◽  
Cloud Data Centers ◽  
Outsourcing Algorithm

The growth of the cloud computing services and its proliferation in business and academia has triggered enormous opportunities for computation in third-party data management settings. This computing model allows the client to outsource their large computations to cloud data centers, where the cloud server conducts the computation on their behalf. But data privacy and computational integrity are the biggest concern for the client. In this article, the authors attempt to present an algorithm for secure outsourcing of a covariance matrix, which is the basic building block for many automatic classification systems. The algorithm first performs some efficient transformation to protect the privacy and verify the computed result produced by the cloud server. Further, an analytical and experimental analysis shows that the algorithm is simultaneously meeting the design goals of privacy, verifiability and efficiency. Also, found that the proposed algorithm is about 7.8276 times more efficient than the direct implementation.

scholarly journals Modified Dynamic Hash Table with Threshold RSA for Dynamic and Public Auditing on Cloud Data

2019 ◽  
Vol 8 (11) ◽  
pp. 765-772
Keyword(s):  
Hash Table ◽  
Third Party ◽  
Experimental Result ◽  
Secret Key ◽  
Computation Cost ◽  
Public Auditing ◽  
Cloud Data ◽  
Major Application ◽  
Rsa Cryptography ◽  
State Of Art

Cloud storage is one of the major application in the cloud, which can provide the on-demand outsourcing data service for both organizations as well as individuals. The Data Integrity (DI) check in the cloud is applied by the user to ensure the integrity of data. The Third Party Auditing (TPA) technique is later introduced to check the cloud DI. Many research has been carried out in the public auditing to minimize the computation cost of the integrity check. The most existing method involves in lack of security and low computation overhead. In this research, the Modified Dynamic Hash Table with threshold Rivest, Shamir, and Adelman Algorithm (RSA) algorithm (MDHT-RSA) is proposed to improve the security and reduce the computation cost. The threshold RSA cryptography system increase the security by generating the secret key to the user and reduce the computation cost. The Modified Dynamic Hash Table (MDHT) is used to record the data information for dynamic auditing, which is located in the TPA. The MDHT is differed from the Dynamic hash table, that the MDHT doesn’t contain the tag block whereas the dynamic hash table has the tag block. The MDHT-RSA is analyzed with the computation cost and compared with existing method. The experimental result proved that the MDHT-RSA method has low computation cost than state-of-art method in public auditing. The verification cost of the MDHT-RSA is 1.3 s while a state-of-art method DHT-PA has the 1.35 s for the 200 blocks of data.

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