scholarly journals An Effective Integrity Verification Scheme of Cloud Data Based on BLS Signature

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Xiling Luo ◽  
Zequan Zhou ◽  
Lin Zhong ◽  
Jian Mao ◽  
Chaoyong Chen
Keyword(s):  
Data Privacy ◽  
Cloud Service ◽  
Privacy Preserving ◽  
Verification Scheme ◽  
Cloud Data ◽  
Integrity Verification ◽  
Main Challenge ◽  
Outsourced Data ◽  
Security Properties ◽  
Local Storage

Cloud storage services allow users to outsource their data remotely to save their local storage space and enable them to manage resources on demand. However, once users outsourced their data to the remote cloud platform, they lose the physical control of the data. How to ensure the integrity of outsourced data is the major concern of cloud users and also is the main challenge in the cloud service deployment. Limited by the communication and computation overheads, traditional hash-based integrity verification solutions in the stand-alone systems cannot be directly adopted in remote cloud storing environment. In this paper, we improve the previous privacy preserving model and propose an effective integrity verification scheme of cloud data based on BLS signature (EoCo), which ensures public audition and data privacy preserving. In addition, EoCo also supports batch auditing operations. We conducted theoretical analysis of our scheme, demonstrated its correctness and security properties, and evaluated the system performance as well.

scholarly journals Public Data Integrity Verification Scheme for Secure Cloud Storage

Information ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 409
Author(s):  
Yuan Ping ◽  
Yu Zhan ◽  
Ke Lu ◽  
Baocang Wang
Keyword(s):  
Cloud Storage ◽  
Data Privacy ◽  
Data Integrity ◽  
Third Party ◽  
Divide And Conquer ◽  
Data Outsourcing ◽  
Verification Scheme ◽  
Integrity Verification ◽  
Outsourced Data ◽  
Public Data

Although cloud storage provides convenient data outsourcing services, an untrusted cloud server frequently threatens the integrity and security of the outsourced data. Therefore, it is extremely urgent to design security schemes allowing the users to check the integrity of data with acceptable computational and communication overheads. In this paper, we first propose a public data integrity verification scheme based on the algebraic signature and elliptic curve cryptography. This scheme not only allows the third party authority deputize for users to verify the outsourced data integrity, but also resists malicious attacks such as replay attacks, replacing attack and forgery attacks. Data privacy is guaranteed by symmetric encryption. Furthermore, we construct a novel data structure named divide and conquer hash list, which can efficiently perform data updating operations, such as deletion, insertion, and modification. Compared with the relevant schemes in the literature, security analysis and performance evaluations show that the proposed scheme gains some advantages in integrity verification and dynamic updating.

A Generic Privacy Breach Preventing Methodology for Cloud Based Web Service

2014 ◽  
Vol 6 (3) ◽  
pp. 53-84 ◽  
Author(s):  
S. R. Murugaiyan ◽  
D. Chandramohan ◽  
T. Vengattaraman ◽  
P. Dhavachelvan
Keyword(s):  
Data Storage ◽  
Private Information ◽  
Data Privacy ◽  
Cloud Service ◽  
Privacy Preserving ◽  
Digital Data ◽  
Cloud Data ◽  
Privacy Breach ◽  
User Data ◽  
Online Storage

The present focuses on the Cloud storage services are having a critical issue in handling the user's private information and its confidentiality. The User data privacy preserving is a vital facet of online storage in cloud computing. The information in cloud data storage is underneath, staid molests of baffling addict endeavor, and it may leads to user clandestine in a roar privacy breach. Moreover, privacy preservation is an indeed research pasture in contemporary information technology development. Preserving User Data in Cloud Service (PUDCS) happens due to the data privacy breach results to a rhythmic way of intruding high confidential digital storage area and barter those information into business by embezzle others information. This paper focuses on preventing (hush-hush) digital data using the proposed privacy preserving framework. It also describes the prevention of stored data and de-identifying unauthorized user attempts, log monitoring and maintaining it in the cloud for promoting allusion to providers and users.

A Generic Privacy Breach Preventing Methodology for Cloud Based Web Service

2015 ◽  
pp. 426-458 ◽  
Author(s):  
S. R. Murugaiyan ◽  
D. Chandramohan ◽  
T. Vengattaraman ◽  
P. Dhavachelvan
Keyword(s):  
Private Information ◽  
Data Privacy ◽  
Privacy Preserving ◽  
Digital Data ◽  
Cloud Data ◽  
Privacy Breach ◽  
Cloud Data Storage ◽  
User Data ◽  
Information Technology Development ◽  
User Data Privacy

The present focuses on the Cloud storage services are having a critical issue in handling the user's private information and its confidentiality. The User data privacy preserving is a vital facet of online storage in cloud computing. The information in cloud data storage is underneath, staid molests of baffling addict endeavor, and it may leads to user clandestine in a roar privacy breach. Moreover, privacy preservation is an indeed research pasture in contemporary information technology development. Preserving User Data in Cloud Service (PUDCS) happens due to the data privacy breach results to a rhythmic way of intruding high confidential digital storage area and barter those information into business by embezzle others information. This paper focuses on preventing (hush-hush) digital data using the proposed privacy preserving framework. It also describes the prevention of stored data and de-identifying unauthorized user attempts, log monitoring and maintaining it in the cloud for promoting allusion to providers and users.

scholarly journals Privacy-Preserving Broker-ABE Scheme for Multiple Cloud-Assisted Cyber Physical Systems

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5463 ◽  
Author(s):  
Po-Wen Chi ◽  
Ming-Hung Wang
Keyword(s):  
Data Privacy ◽  
Service Providers ◽  
Real Life ◽  
Data Communication ◽  
Physical Space ◽  
Cloud Service ◽  
Cyber Physical Systems ◽  
Privacy Preserving ◽  
Sensor Data ◽  
Physical Systems

Cloud-assisted cyber–physical systems (CCPSs) integrate the physical space with cloud computing. To do so, sensors on the field collect real-life data and forward it to clouds for further data analysis and decision-making. Since multiple services may be accessed at the same time, sensor data should be forwarded to different cloud service providers (CSPs). In this scenario, attribute-based encryption (ABE) is an appropriate technique for securing data communication between sensors and clouds. Each cloud has its own attributes and a broker can determine which cloud is authorized to access data by the requirements set at the time of encryption. In this paper, we propose a privacy-preserving broker-ABE scheme for multiple CCPSs (MCCPS). The ABE separates the policy embedding job from the ABE task. To ease the computational burden of the sensors, this scheme leaves the policy embedding task to the broker, which is generally more powerful than the sensors. Moreover, the proposed scheme provides a way for CSPs to protect data privacy from outside coercion.

scholarly journals A Privacy Preserving Cloud-Based K-NN Search Scheme with Lightweight User Loads

Computers ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 1 ◽  
Author(s):  
Yeong-Cherng Hsu ◽  
Chih-Hsin Hsueh ◽  
Ja-Ling Wu
Keyword(s):  
Data Privacy ◽  
Nearest Neighbor ◽  
Search Algorithm ◽  
Data Access ◽  
Privacy Preserving ◽  
Secret Key ◽  
K Nearest Neighbor ◽  
Sensitive Data ◽  
Cloud Data ◽  
Cloud Server

With the growing popularity of cloud computing, it is convenient for data owners to outsource their data to a cloud server. By utilizing the massive storage and computational resources in cloud, data owners can also provide a platform for users to make query requests. However, due to the privacy concerns, sensitive data should be encrypted before outsourcing. In this work, a novel privacy preserving K-nearest neighbor (K-NN) search scheme over the encrypted outsourced cloud dataset is proposed. The problem is about letting the cloud server find K nearest points with respect to an encrypted query on the encrypted dataset, which was outsourced by data owners, and return the searched results to the querying user. Comparing with other existing methods, our approach leverages the resources of the cloud more by shifting most of the required computational loads, from data owners and query users, to the cloud server. In addition, there is no need for data owners to share their secret key with others. In a nutshell, in the proposed scheme, data points and user queries are encrypted attribute-wise and the entire search algorithm is performed in the encrypted domain; therefore, our approach not only preserves the data privacy and query privacy but also hides the data access pattern from the cloud server. Moreover, by using a tree structure, the proposed scheme could accomplish query requests in sub-liner time, according to our performance analysis. Finally, experimental results demonstrate the practicability and the efficiency of our method.

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 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.  

scholarly journals PPK-Means: Achieving Privacy-Preserving Clustering Over Encrypted Multi-Dimensional Cloud Data

Electronics ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 310 ◽  
Author(s):  
Hui Yin ◽  
Jixin Zhang ◽  
Yinqiao Xiong ◽  
Xiaofeng Huang ◽  
Tiantian Deng
Keyword(s):  
Cloud Computing ◽  
Data Clustering ◽  
Data Privacy ◽  
Real Life ◽  
Data Encryption ◽  
Privacy Preserving ◽  
Data Sets ◽  
Cloud Data ◽  
Practical Applications ◽  
Computing Paradigm

Clustering is a fundamental and critical data mining branch that has been widely used in practical applications such as user purchase model analysis, image color segmentation, outlier detection, and so on. With the increasing popularity of cloud computing, more and more encrypted data are converging to cloud computing platforms for enjoying the revolutionary advantages of the cloud computing paradigm, as well as mitigating the deeply concerned data privacy issues. However, traditional data encryption makes existing clustering schemes no more effective, which greatly obstructs effective data utilization and frustrates the wide adoption of cloud computing. In this paper, we focus on solving the clustering problem over encrypted cloud data. In particular, we propose a privacy-preserving k-means clustering technology over encrypted multi-dimensional cloud data by leveraging the scalar-product-preserving encryption primitive, called PPK-means. The proposed technique is able to achieve efficient multi-dimensional data clustering as well to preserve the confidentiality of the outsourced cloud data. To the best of our knowledge, our work is the first to explore the privacy-preserving multi-dimensional data clustering in the cloud computing environment. Extensive experiments in simulation data-sets and real-life data-sets demonstrate that our proposed PPK-means is secure, efficient, and practical.

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