scholarly journals A Quantum-Based Database Query Scheme for Privacy Preservation in Cloud Environment

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Wenjie Liu ◽  
Peipei Gao ◽  
Zhihao Liu ◽  
Hanwu Chen ◽  
Maojun Zhang
Keyword(s):  
Data Privacy ◽  
Privacy Preservation ◽  
Communication Complexity ◽  
Data Item ◽  
Data Service ◽  
Cloud Environment ◽  
Database Query ◽  
Encrypted Data ◽  
Cloud Data ◽  
Management Effort

Cloud computing is a powerful and popular information technology paradigm that enables data service outsourcing and provides higher-level services with minimal management effort. However, it is still a key challenge to protect data privacy when a user accesses the sensitive cloud data. Privacy-preserving database query allows the user to retrieve a data item from the cloud database without revealing the information of the queried data item, meanwhile limiting user’s ability to access other ones. In this study, in order to achieve the privacy preservation and reduce the communication complexity, a quantum-based database query scheme for privacy preservation in cloud environment is developed. Specifically, all the data items of the database are firstly encrypted by different keys for protecting server’s privacy, and in order to guarantee the clients’ privacy, the server is required to transmit all these encrypted data items to the client with the oblivious transfer strategy. Besides, two oracle operations, a modified Grover iteration, and a special offset encryption mechanism are combined together to ensure that the client can correctly query the desirable data item. Finally, performance evaluation is conducted to validate the correctness, privacy, and efficiency of our proposed scheme.

scholarly journals A Review on Secure Storage Using Bidirectional Verification Techniques in Cloud Computing

2018 ◽  
Vol 7 (4.36) ◽  
pp. 511
Author(s):  
Mr. Girish kumar d ◽  
Dr. Rajashree v biradar ◽  
Dr. V c patil
Keyword(s):  
Cloud Computing ◽  
Data Privacy ◽  
Virtual Machines ◽  
Cloud Service ◽  
Sensitive Information ◽  
Cloud Environment ◽  
It Industry ◽  
Cloud Data ◽  
Secure Storage ◽  
Verification Techniques

Cloud computing increases the capacity or capabilities vigorously without devoting new infrastructure, training new personnel, or licensing the new software . In the past few years, cloud computing has grown from being a promising business concept to one of the fast-growing sectors of IT industry. As the more sensitive information and data are moved into the cloud data centers, they run on virtual computing resources in the form of virtual machines. Security has become one of the major issue in cloud computing which reduces the growth of cloud environment with complications in data privacy and data protection continue to outbreak the market. A new model created for the advancement should not result as a threat to the existing model. The architecture of cloud poses such a threat to the security of existing models when deployed in a cloud environment. The different cloud service users need to be attentive in considerate,about the risk of data breaks in the new environment. In this paper, advanced survey of the various secured storage in cloud computing using bidirectional protocols is presented.  

scholarly journals Data Privacy Preservation using AES-GCM Encryption in Heroku Cloud

2019 ◽  
Vol 8 (3) ◽  
pp. 7544-7548
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Data Privacy ◽  
Privacy Preservation ◽  
Service Industry ◽  
Computational Cost ◽  
Cloud Service ◽  
Third Party ◽  
Sensitive Information ◽  
Cloud Data

The increasing popularity of cloud data storage and its ever-rising versatility, shows that cloud computing is one of the most widely excepted phenomena. It not only helps with powerful computing facilities but also reduce a huge amount of computational cost. And with such high demand for storage has raised the growth of the cloud service industry that provides an affordable, easy-to-use and remotely-accessible services. But like every other emerging technology it carries some inherent security risks associated and cloud storage is no exception. The prime reason behind it is that users have to blindly trust the third parties while storing the useful information, which may not work in the best of interest. Hence, to ensure the privacy of sensitive information is primarily important for any public, third-party cloud. In this paper, we mainly focus on proposing a secure cloud framework with encrypting sensitive data’s using AES-GCM cryptographic techniques in HEROKU cloud platform. Here we tried to implement Heroku as a cloud computing platform, used the AES-GCM algorithm and evaluate the performance of the said algorithm. Moreover, analyses the performance of AES/GCM execution time with respect to given inputs of data

scholarly journals Mobile Cloud Data Privacy using Lightweight Data Sharing System

2019 ◽  
Vol 8 (4) ◽  
pp. 8137-8141
Keyword(s):  
Access Control ◽  
Data Sharing ◽  
Data Privacy ◽  
Cloud Service ◽  
Mobile Cloud ◽  
Cloud Environment ◽  
Cloud Data ◽  
Security Problem ◽  
Share Data ◽  
Control Tree

The data security problem in mobile cloud becomes more and more severe and it prevents further development of mobile cloud. There are substantial studies that have been conducted to improve the cloud security. However the most of them are not applicable for mobile cloud since mobile devices only have limited computing resources and power. So we propose a light weight data sharing scheme (LDSS) for mobile computing it adopts CP-ABE (Cipher text policy attribute based encryption) an access control technology using normal cloud environment but changes a structure of access control tree to make suitable for mobile cloud environment. It is important to use the resources provided by Cloud Service Provide to store and share data. Thus LDSS can effectively reduce the over head on the mobile device side when users are sharing a data in mobile cloud environment..

scholarly journals A COMPARATIVE STUDY OF ZERO KNOWLEDGE PROOF AND HOMOMORPHIC ENCRYPTION IN GUARANTEEING DATA PRIVACY IN BLOCKCHAIN APPLICATIONS

2021 ◽  
Vol 9 (02) ◽  
pp. 359-361
Author(s):  
Liz George ◽  
◽  
Jubilant J. Kizhakkethottam ◽  
Keyword(s):  
Comparative Study ◽  
Data Privacy ◽  
Privacy Preservation ◽  
Homomorphic Encryption ◽  
Zero Knowledge ◽  
Encrypted Data ◽  
Block Chain ◽  
Zero Knowledge Proof

Homomorphic Encryption and Zero Knowledge Proofs are two trending concepts that are widely popular as data privacy preservation techniques in a wide variety of applications, especially in those associated with the newly evolved block chain technology which are immutable, distributed and secure. Zero knowledge proof is a cryptographic technique can provide proof that a certain statement is correct, without revealing any details about the statement, while homomorphic encryption allows to perform computations on encrypted data without decrypting it. This article explores the significance of the data privacy aspect provided by both ZKP and Homomorphic Encryption and how it can be effectively used to improvise the privacy of blockchain applications in various domains.

scholarly journals Variable Techniques for Ciphertext Retrieval through Encrypted Data

2019 ◽  
Vol 8 (12) ◽  
pp. 3477-3479
Keyword(s):  
Cloud Storage ◽  
Data Privacy ◽  
Large Scale ◽  
Keyword Search ◽  
Maximum Size ◽  
Data Retrieval ◽  
Sensitive Data ◽  
Data Utilization ◽  
Encrypted Data ◽  
Cloud Data

In recent years, Cloud computing provides strong grip and flexible access on outsource data, cloud storage, data privacy is major concern from to outsource their data, authenticated users are allowed to access this storage to prevent important and sensitive data. For data protection and utilization, we encrypt our sensitive data before outsourced our data because cannot trust storage server, are un-trusty but on other hand, data retrieval in encrypted format from cloud, is challenging task for data utilization, was encrypted from plaintext to ciphertext, when retrieves from cloud storage. However, searchable encryption schemes used Boolean search but they are unable to make data utilization for huge data and failed to handle multi-users access to retrieve ciphertext from cloud and user’s authentication. In this paper, we are using ranked keyword search over encrypted data by going k-documents at storage and using a Hierarchical Clustering Method is designed to guide more search semantics with an additional feature of making the system to cope the demand for fast ciphertext k-search in large scale environments explored the relevance score such as massive and big cloud data. This threshold splits the consequential clusters into sub-clusters until the necessity on the maximum size of cluster is reached. To make fetching search to be secure and privacy-preserving, it is built an index for searching on cloud data and retrieve the most relevant files from cloud. To defending privacy breaches from unauthorized users, users will go through authentication process and data retrieval time as well.

scholarly journals Data Integrity, Data Privacy and Data Confidentiality Issues in Multi-User Cloud

2019 ◽  
Vol 8 (6) ◽  
pp. 1705-1708
Keyword(s):  
Data Privacy ◽  
Computational Models ◽  
The Other ◽  
Cloud Environment ◽  
Data Confidentiality ◽  
Cloud Data ◽  
Cloud Server ◽  
Secure Environment ◽  
Current Scenario ◽  
Privacy And Confidentiality

Cloud computing was one of the most significant computational models that help to handle the vast amount of data in a flexible and secure environment. In the current scenario, the amount of data being shared and the number of users or group in the cloud has been continuously increasing. The rise in the usage of the clouds had instigated the need to provide the security to the data that were transmitted among the user and owner through a cloud server. The data in the cloud most commonly endure in issues related to the integrity, privacy, and confidentiality (IPC). This paper was the accumulation of extensive research works to resist the issues in the clouds. Many researchers had indulged in the process of enhancing the security of the cloud data by generating the keys, performing the cryptic mechanisms, auditing, de-duplication techniques, enhancement in handling the queries and many more approaches. The outcomes from the some works are discussed with other approaches to understand the objective accomplished by each work over the other. The general IPC issue and challenges exist in the cloud environment were listed and it was identified that there is a necessity for the better methodology to accomplish the robust cloud environment

Control Cloud Data Access Privilge Anonymity with Attributed Based Encryption

2017 ◽  
Vol 7 (8) ◽  
pp. 279
Author(s):  
P. Sudheer ◽  
T. Lakshmi Surekha
Keyword(s):  
Data Privacy ◽  
Low Cost ◽  
Data Access ◽  
Privacy Concerns ◽  
Cloud Data ◽  
Computing Paradigm ◽  
Attribute Based Encryption ◽  
Data Content ◽  
Identity Privacy ◽  
Cloud Servers

Cloud computing is a revolutionary computing paradigm, which enables flexible, on-demand, and low-cost usage of computing resources, but the data is outsourced to some cloud servers, and various privacy concerns emerge from it. Various schemes based on the attribute-based encryption have been to secure the cloud storage. Data content privacy. A semi anonymous privilege control scheme AnonyControl to address not only the data privacy. But also the user identity privacy. AnonyControl decentralizes the central authority to limit the identity leakage and thus achieves semi anonymity. The  Anonymity –F which fully prevent the identity leakage and achieve the full anonymity.

Enhanced Data Security from Single Clouds to Multiclouds

2018 ◽  
Vol 6 (9) ◽  
pp. 66
Author(s):  
Umesh Banodha ◽  
Praveen Kumar Kataria
Keyword(s):  
Data Storage ◽  
Network Connectivity ◽  
Data Replication ◽  
Recovery Process ◽  
Cloud Environment ◽  
Storage Security ◽  
Cloud Data ◽  
Replication Strategy ◽  
Cloud Data Storage ◽  
Data Files

Cloud is an emerging technology that stores the necessary data and electronic form of data is produced in gigantic quantity. It is vital to maintain the efficacy of this data the need of data recovery services is highly essential. Cloud computing is anticipated as the vital foundation for the creation of IT enterprise and it is an impeccable solution to move databases and application software to big data centers where managing data and services is not completely reliable. Our focus will be on the cloud data storage security which is a vital feature when it comes to giving quality service. It should also be noted that cloud environment comprises of extremely dynamic and heterogeneous environment and because of high scale physical data and resources, the failure of data centre nodes is completely normal.Therefore, cloud environment needs effective adaptive management of data replication to handle the indispensable characteristic of the cloud environment. Disaster recovery using cloud resources is an attractive approach and data replication strategy which attentively helps to choose the data files for replication and the strategy proposed tells dynamically about the number of replicas and effective data nodes for replication. Thus, the objective of future algorithm is useful to help users together the information from a remote location where network connectivity is absent and secondly to recover files in case it gets deleted or wrecked because of any reason. Even, time oriented problems are getting resolved so in less time recovery process is executed.

Big Data Privacy Preservation Using Two Phase Top-Down Specialization Algorithm with Multidimensional Map Reduce Framework on Hadoop

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
Shalin Eliabeth S. ◽  
Sarju S.
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
Privacy Preservation ◽  
Experimental Result ◽  
Map Reduce ◽  
Distributed Environment ◽  
Top Down ◽  
Two Phase ◽  
Data Anonymization ◽  
Big Data Privacy

Big data privacy preservation is one of the most disturbed issues in current industry. Sometimes the data privacy problems never identified when input data is published on cloud environment. Data privacy preservation in hadoop deals in hiding and publishing input dataset to the distributed environment. In this paper investigate the problem of big data anonymization for privacy preservation from the perspectives of scalability and time factor etc. At present, many cloud applications with big data anonymization faces the same kind of problems. For recovering this kind of problems, here introduced a data anonymization algorithm called Two Phase Top-Down Specialization (TPTDS) algorithm that is implemented in hadoop. For the data anonymization-45,222 records of adults information with 15 attribute values was taken as the input big data. With the help of multidimensional anonymization in map reduce framework, here implemented proposed Two-Phase Top-Down Specialization anonymization algorithm in hadoop and it will increases the efficiency on the big data processing system. By conducting experiment in both one dimensional and multidimensional map reduce framework with Two Phase Top-Down Specialization algorithm on hadoop, the better result shown in multidimensional anonymization on input adult dataset. Data sets is generalized in a top-down manner and the better result was shown in multidimensional map reduce framework by the better IGPL values generated by the algorithm. The anonymization was performed with specialization operation on taxonomy tree. The experiment shows that the solutions improves the IGPL values, anonymity parameter and decreases the execution time of big data privacy preservation by compared to the existing algorithm. This experimental result will leads to great application to the distributed environment.

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