scholarly journals Obfuscating encrypted threshold signature algorithm and its applications in cloud computing

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250259
Author(s):  
Yahong Li ◽  
Jianzhou Wei ◽  
Bin Wu ◽  
Chunli Wang ◽  
Caifen Wang ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Privacy ◽  
Service Providers ◽  
Sensitive Information ◽  
Threshold Signature ◽  
Sensitive Data ◽  
Average Case ◽  
Diffie Hellman ◽  
Program Obfuscation ◽  
Pairing Based Cryptography

Current cloud computing causes serious restrictions to safeguarding users’ data privacy. Since users’ sensitive data is submitted in unencrypted forms to remote machines possessed and operated by untrusted service providers, users’ sensitive data may be leaked by service providers. Program obfuscation shows the unique advantages that it can provide for cloud computing. In this paper, we construct an encrypted threshold signature functionality, which can outsource the threshold signing rights of users to cloud server securely by applying obfuscation, while revealing no more sensitive information. The obfuscator is proven to satisfy the average case virtual black box property and existentially unforgeable under the decisional linear (DLIN) assumption and computational Diffie-Hellman (CDH) assumption in the standard model. Moreover, we implement our scheme using the Java pairing-based cryptography library on a laptop.

scholarly journals Redistributed Records Collections Personality Matching using Encrypted Cryptosystem

2019 ◽  
Vol 8 (12S) ◽  
pp. 1234-1236
Keyword(s):  
Cloud Computing ◽  
Data Privacy ◽  
Data Sets ◽  
Sensitive Information ◽  
Sensitive Data ◽  
Encrypted Data ◽  
Use Of Data ◽  
Private Matching ◽  
Personality Matching

Sensitive information is gradually distributed in the cloud in this project's cloud computing and processing services to reduce costs, which raises concerns regarding data privacy. Encryption was a positive way to keep outsourced sensitive data secure, but it makes efficient use of data a very difficult process. In this paper, we focus on the issue of private matching in ide ntity-based cryptosystem over outsourced encrypted data sets that can simplify the management of certificates. To solve this proble m, we are proposing a private matching scheme based on identity

scholarly journals The Challenges of Institutional Distance: Data Privacy Issues in Cloud Computing

2018 ◽  
Vol 24 (1) ◽  
pp. 161-181 ◽  
Author(s):  
Yashar Abed ◽  
Meena Chavan
Keyword(s):  
Cloud Computing ◽  
Multinational Corporations ◽  
Data Privacy ◽  
Service Providers ◽  
Host Countries ◽  
Case Study Methodology ◽  
Regulatory Constraints ◽  
Cloud Computing Service ◽  
Privacy Issues

Data protection and data privacy are significant challenges in cloud computing for multinational corporations. There are no standard laws to protect data across borders. The institutional and regulatory constraints and governance differ across countries. This article explores the challenges of institutional constraints faced by cloud computing service providers in regard to data privacy issues across borders. Through a qualitative case study methodology, this research compares the institutional structure of a few host countries, with regard to data privacy in cloud computing and delineates a relative case study. This article will also review the cloud computing legal frameworks and the history of cloud computing to make the concept more comprehensible to a layman.

scholarly journals A Secure Ciphertext Retrieval Scheme against Insider KGAs for Mobile Devices in Cloud Storage

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Run Xie ◽  
Chanlian He ◽  
Dongqing Xie ◽  
Chongzhi Gao ◽  
Xiaojun Zhang
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Data Privacy ◽  
Security Analysis ◽  
Data Retrieval ◽  
Sensitive Data ◽  
Encrypted Data ◽  
Security Issues ◽  
Efficiency Comparison ◽  
Cloud Servers

With the advent of cloud computing, data privacy has become one of critical security issues and attracted much attention as more and more mobile devices are relying on the services in cloud. To protect data privacy, users usually encrypt their sensitive data before uploading to cloud servers, which renders the data utilization to be difficult. The ciphertext retrieval is able to realize utilization over encrypted data and searchable public key encryption is an effective way in the construction of encrypted data retrieval. However, the previous related works have not paid much attention to the design of ciphertext retrieval schemes that are secure against inside keyword-guessing attacks (KGAs). In this paper, we first construct a new architecture to resist inside KGAs. Moreover we present an efficient ciphertext retrieval instance with a designated tester (dCRKS) based on the architecture. This instance is secure under the inside KGAs. Finally, security analysis and efficiency comparison show that the proposal is effective for the retrieval of encrypted data in cloud computing.

scholarly journals eHealth Cloud Security Challenges: A Survey

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Yazan Al-Issa ◽  
Mohammad Ashraf Ottom ◽  
Ahmed Tamrawi
Keyword(s):  
Cloud Computing ◽  
Resource Sharing ◽  
Energy Savings ◽  
Service Providers ◽  
Healthcare Providers ◽  
Cloud Service ◽  
Cloud Security ◽  
Security And Privacy ◽  
Healthcare Industry ◽  
Sensitive Data

Cloud computing is a promising technology that is expected to transform the healthcare industry. Cloud computing has many benefits like flexibility, cost and energy savings, resource sharing, and fast deployment. In this paper, we study the use of cloud computing in the healthcare industry and different cloud security and privacy challenges. The centralization of data on the cloud raises many security and privacy concerns for individuals and healthcare providers. This centralization of data (1) provides attackers with one-stop honey-pot to steal data and intercept data in-motion and (2) moves data ownership to the cloud service providers; therefore, the individuals and healthcare providers lose control over sensitive data. As a result, security, privacy, efficiency, and scalability concerns are hindering the wide adoption of the cloud technology. In this work, we found that the state-of-the art solutions address only a subset of those concerns. Thus, there is an immediate need for a holistic solution that balances all the contradicting requirements.

An Approach to Data Confidentiality Protection in Cloud Environments

2012 ◽  
Vol 9 (3) ◽  
pp. 67-83 ◽  
Author(s):  
Stephen S. Yau ◽  
Ho G. An ◽  
Arun Balaji Buduru
Keyword(s):  
Cloud Computing ◽  
Data Processing ◽  
Data Storage ◽  
Service Providers ◽  
Data Confidentiality ◽  
Sensitive Data ◽  
Computing Systems ◽  
Cloud Application ◽  
Cloud Infrastructures ◽  
Processing Service

In current cloud computing systems, because users’ data is stored and processed by computing systems managed and operated by various service providers, users are concerned with the risks of unauthorized usage of their sensitive data by various entities, including service providers. The current cloud computing systems protect users’ data confidentiality from all entities, except service providers. In this paper, an approach is presented for improving the protection of users’ data confidentiality in cloud computing systems from all entities, including service providers. The authors’ approach has the following features: (1) separation of cloud application providers, data processing service providers and data storage providers, (2) anonymization of users’ identities, (3) grouping cloud application components and distributing their execution to distinct cloud infrastructures of data processing service providers, and (4) use of data obfuscation and cryptography for protecting the sensitive data from unauthorized access by all entities, including service providers. The proposed approach ensures that users’ sensitive data can be protected from their service providers even if the users do not have full cooperation from their service providers.

Enforcing Data Privacy in Outsourced Database Services

2011 ◽  
Vol 255-260 ◽  
pp. 2224-2228
Author(s):  
Yong Hong Yu ◽  
Wen Yang Bai
Keyword(s):  
Data Privacy ◽  
Service Providers ◽  
Sensitive Information ◽  
Relational Schema ◽  
Outsourced Data ◽  
Real World Applications ◽  
Networking Technologies ◽  
Privacy Constraints ◽  
Definition Of ◽  
Outsourced Database

Advances in networking technologies and the continued growth of the internet have triggered a new trend towards outsourcing data management and information technology needs to external service providers, and privacy requirements have an increasing impact on such real-world applications. In this paper, we propose a solution to enforce data privacy over outsourced database services. The approach starts from a flexible definition of privacy constraints on a relational schema, applies encryption on information in parsimonious way and mostly relies on attribute partition to protect sensitive information. Based on the approximation algorithm for the minimal encryption of attribute partition and the decomposition of SQL queries, the approach allows storing the outsourced data on a single database server and minimizing the amount of data represented in encrypted format, and allows executing queries over encrypted outsourced database efficiently.

scholarly journals Privacy enforcement on subscribers data in cloud computing

2021 ◽  
Vol 40 (2) ◽  
pp. 308-320
Author(s):  
S.A. Akinboro ◽  
U.J. Asanga ◽  
M.O. Abass
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Provider ◽  
Sensitive Information ◽  
Secure Socket Layer ◽  
Brute Force ◽  
User Privacy ◽  
Platform As A Service ◽  
High Level

Data stored in the cloud are susceptible to an array of threats from hackers. This is because threats, hackers and unauthorized access are not supported by the cloud service providers as implied. This study improves user privacy in the cloud system, using privacy with non-trusted provider (PNTP) on software and platform as a service model. The subscribers encrypt the data using user’s personal Advanced Encryption Standard (AES) symmetric key algorithm and send the encrypted data to the storage pool of the Cloud Service Provider (CSP) via a secure socket layer. The AES performs a second encryption on the data sent to the cloud and generates for the subscriber a key that will be used for decryption of previously stored data. The encryption and decryption keys are managed by the key server and have been hardcoded into the PNTP system. The model was simulated using the Stanford University multimedia dataset and benchmarked with a Privacy with Trusted cloud Provider (PTP) model using encryption time, decryption time and efficiency (brute force hacking) as parameters. Results showed that it took a longer time to access the user files in PNTP than in the PTP system. The brute force hacking took a longer time (almost double) to access data stored on the PNTP system. This will give subscribers a high level of control over their data and increase the adoption of cloud computing by businesses and organizations with highly sensitive information.

scholarly journals USING DIFFERENT SEARCHING SCHEMAS FOR FUZZY KEYWORD SEARCH OVER CLOUD DATA

2013 ◽  
pp. 41-44
Author(s):  
SYEDA FARHA SHAZMEEN ◽  
RANGARAJU DEEPIKA
Keyword(s):  
Cloud Computing ◽  
Data Privacy ◽  
Keyword Search ◽  
Text Search ◽  
Sensitive Data ◽  
Cloud Data ◽  
Fuzzy Search ◽  
Wild Card ◽  
Fuzzy Keyword Search ◽  
Search And Retrieval

Cloud Computing is a construct that allows you to access applications that actually reside at a location other than our computer or other internet-connected devices, Cloud computing uses internet and central remote servers to maintain data and applications, the data is stored in off-premises and accessing this data through keyword search. So there comes the importance of encrypted cloud data search Traditional keyword search was based on plaintext keyword search, but for protecting data privacy the sensitive data should be encrypted before outsourcing. Fuzzy keyword search greatly enhances system usability by returning the matching files; Fuzzy technique uses approximate full text search and retrieval. Three different Fuzzy Search Schemas, The wild card method, gram based method and tree traverse search scheme, are dicussed and also the efficiency of these algorithms is analyzed.

scholarly journals Data Privacy Preservation and Security Approaches for Sensitive Data in Big Data

2021 ◽  
Author(s):  
Rohit Ravindra Nikam ◽  
Rekha Shahapurkar
Keyword(s):  
Data Mining ◽  
Data Analytics ◽  
Data Privacy ◽  
Privacy Preservation ◽  
Large Data ◽  
Research Area ◽  
Data Sets ◽  
Sensitive Information ◽  
Sensitive Data ◽  
Data Mining Techniques

Data mining is a technique that explores the necessary data is extracted from large data sets. Privacy protection of data mining is about hiding the sensitive information or identity of breach security or without losing data usability. Sensitive data contains confidential information about individuals, businesses, and governments who must not agree upon before sharing or publishing his privacy data. Conserving data mining privacy has become a critical research area. Various evaluation metrics such as performance in terms of time efficiency, data utility, and degree of complexity or resistance to data mining techniques are used to estimate the privacy preservation of data mining techniques. Social media and smart phones produce tons of data every minute. To decision making, the voluminous data produced from the different sources can be processed and analyzed. But data analytics are vulnerable to breaches of privacy. One of the data analytics frameworks is recommendation systems commonly used by e-commerce sites such as Amazon, Flip Kart to recommend items to customers based on their purchasing habits that lead to characterized. This paper presents various techniques of privacy conservation, such as data anonymization, data randomization, generalization, data permutation, etc. such techniques which existing researchers use. We also analyze the gap between various processes and privacy preservation methods and illustrate how to overcome such issues with new innovative methods. Finally, our research describes the outcome summary of the entire literature.

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.  

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