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 Privacy-Preserving Sorting Algorithms Based on Logistic Map for Clouds

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Hua Dai ◽  
Hui Ren ◽  
Zhiye Chen ◽  
Geng Yang ◽  
Xun Yi
Keyword(s):  
Data Privacy ◽  
Logistic Map ◽  
Security Analysis ◽  
Privacy Preserving ◽  
Service Recommendation ◽  
Sensitive Data ◽  
Encrypted Data ◽  
Sorting Algorithms ◽  
Common Operation ◽  
Cloud Servers

Outsourcing data in clouds is adopted by more and more companies and individuals due to the profits from data sharing and parallel, elastic, and on-demand computing. However, it forces data owners to lose control of their own data, which causes privacy-preserving problems on sensitive data. Sorting is a common operation in many areas, such as machine learning, service recommendation, and data query. It is a challenge to implement privacy-preserving sorting over encrypted data without leaking privacy of sensitive data. In this paper, we propose privacy-preserving sorting algorithms which are on the basis of the logistic map. Secure comparable codes are constructed by logistic map functions, which can be utilized to compare the corresponding encrypted data items even without knowing their plaintext values. Data owners firstly encrypt their data and generate the corresponding comparable codes and then outsource them to clouds. Cloud servers are capable of sorting the outsourced encrypted data in accordance with their corresponding comparable codes by the proposed privacy-preserving sorting algorithms. Security analysis and experimental results show that the proposed algorithms can protect data privacy, while providing efficient sorting on encrypted data.

scholarly journals An efficient and secure data sharing scheme for mobile devices in cloud computing

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Xiuqing Lu ◽  
Zhenkuan Pan ◽  
Hequn Xian
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Data Sharing ◽  
Data Privacy ◽  
Mobile Terminals ◽  
Sensitive Data ◽  
Integrity Verification ◽  
Sharing Scheme ◽  
Secure Data ◽  
Authorized Access

Abstract With the development of big data and cloud computing, more and more enterprises prefer to store their data in cloud and share the data among their authorized employees efficiently and securely. So far, many different data sharing schemes in different fields have been proposed. However, sharing sensitive data in cloud still faces some challenges such as achieving data privacy and lightweight operations at resource constrained mobile terminals. Furthermore, most data sharing schemes have no integrity verification mechanism, which would result in wrong computation results for users. To solve the problems, we propose an efficient and secure data sharing scheme for mobile devices in cloud computing. Firstly, the scheme guarantees security and authorized access of shared sensitive data. Secondly, the scheme realizes efficient integrity verification before users share the data to avoid incorrect computation. Finally, the scheme achieves lightweight operations of mobile terminals on both data owner and data requester sides.

scholarly journals Enhance manet usability for encrypted data retrieval from cloud computing

2020 ◽  
Vol 18 (1) ◽  
pp. 64
Author(s):  
Fairouz Sher Ali ◽  
Hadeel Noori Saad ◽  
Falah Hassan Sarhan ◽  
Bushra Naaeem
Keyword(s):  
Cloud Computing ◽  
Mobile Networks ◽  
Resource Sharing ◽  
Keyword Search ◽  
Bloom Filter ◽  
Data Retrieval ◽  
Mobile Nodes ◽  
Sensitive Data ◽  
Privacy Concerns ◽  
Cloud Servers

<p>Cloud computing has become a revolutionary computing model which provides an economical and flexible strategy for resource sharing and data management. Due to privacy concerns, sensitive data has to be encrypted before being uploaded to the cloud servers. Over the last few years, several keyword searchable encryption works have been described in the literature. However, existing works mostly focus on secure searching using keyword and only retrieve Boolean results that are not yet adequate. On the other hand, poor-resources of mobile networks play an important role on all applications area nowadays. Mobile nodes mostly act as information retrieval end which make it important to address this problem. In this paper, we present a secure keyword search scheme based on the Bloom filter(SKS-BF), which enhances the system’s usability by allowing ranking based on the relevance score of the search results and retrieves the top most relevant files instead of retrieving all the files. Further, the Bloom filter (BFs) can accelerate a search process involving a large number of keywords. Extensive experiments and network simulation confirm the efficiency of our proposed schemes.</p>

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 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 Research gaps based virtualization in mobile cloud computing

2020 ◽  
Vol 10 (51) ◽  
pp. 212-222
Author(s):  
Boubakeur Annane ◽  
Adel Alti ◽  
Osman Ghazali
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Mobile Cloud Computing ◽  
Virtual Machines ◽  
Cloud Services ◽  
Security And Privacy ◽  
Battery Life ◽  
Mobile Cloud ◽  
Sensitive Data ◽  
Cloud Servers

Recently, mobile computing is known as a fast-growing utilization of people's daily life. However, the main is the limited mobile devices’ resources such as processing capability, storage space and battery life. With the development of cloud computing, mobile devices’ resources are improved with the help of cloud services, which resulted an emerged technology named Mobile Cloud Computing (MCC). Although the MCC has several advantages for mobile users, it is also challenged by many critical issues like security and privacy of the mobile user's data that offloaded on the cloud’ servers and processed on the virtual machines (VMs). In virtualization, various investigations showed that malicious users are able to break down the cloud security methods by spreading their VMs in order to alter or violate the user sensitive data that executed on cloud’ VMs. This paper deeply analyzes the recent MCC based virtualization approaches and methods by criticizing them. We found out that no approach protects the data from being stolen while distributed VMs that deployed on different cloud servers exchanging data. Hence, the paper provides practical gaps related to virtualization in MCC and future perspectives.

scholarly journals Client/Server Model of Data Privacy using Extended Playfair Cipher for SaaS Applications on the Cloud

2019 ◽  
Vol 8 (10) ◽  
pp. 1933-1936 ◽  
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Data Privacy ◽  
Cloud Model ◽  
Cloud Services ◽  
Sensitive Data ◽  
The Public ◽  
Security Issues ◽  
On Demand ◽  
Self Service

Cloud Computing is a paradigm of distributed computing that delivers on-demand and utility-based services to its customers. It provides a set of shared computing resources such as networking, servers, storage, and applications in the form of services to an organization or an individual. The major benefits of cloud computing include on-demand self-service and cost-effectiveness. For the customer, there is no up-front cost for setting up and running the applications on the cloud. Despite the benefits provided by various cloud services, the outsourcing of data storage and computation raise many new security issues. One of such security issues that have to be addressed before uploading our sensitive data to the cloud is data privacy. With the cloud model, end-users lose control over the physical location of data, because data will be stored and processed elsewhere on the globe and not in the local computer. Hence, we need an algorithm for encrypting the data that can be stored and retrieved from a database managed by the public cloud.

scholarly journals PMDP: A Framework for Preserving Multiparty Data Privacy in Cloud Computing

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Ji Li ◽  
Jianghong Wei ◽  
Wenfen Liu ◽  
Xuexian Hu
Keyword(s):  
Cloud Computing ◽  
Data Privacy ◽  
Differential Privacy ◽  
Security Analysis ◽  
Cost Effective ◽  
Original Data ◽  
User Privacy ◽  
Practical Applications ◽  
Cloud Servers ◽  
Privacy Issues

The amount of Internet data is significantly increasing due to the development of network technology, inducing the appearance of big data. Experiments have shown that deep mining and analysis on large datasets would introduce great benefits. Although cloud computing supports data analysis in an outsourced and cost-effective way, it brings serious privacy issues when sending the original data to cloud servers. Meanwhile, the returned analysis result suffers from malicious inference attacks and also discloses user privacy. In this paper, to conquer the above privacy issues, we propose a general framework for Preserving Multiparty Data Privacy (PMDP for short) in cloud computing. The PMDP framework can protect numeric data computing and publishing with the assistance of untrusted cloud servers and achieve delegation of storage simultaneously. Our framework is built upon several cryptography primitives (e.g., secure multiparty computation) and differential privacy mechanism, which guarantees its security against semihonest participants without collusion. We further instantiate PMDP with specific algorithms and demonstrate its security, efficiency, and advantages by presenting security analysis and performance discussion. Moreover, we propose a security enhanced framework sPMDP to resist malicious inside participants and outside adversaries. We illustrate that both PMDP and sPMDP are reliable and scale well and thus are desirable for practical applications.

Mobile Cloud Computing

2018 ◽  
pp. 105-123
Author(s):  
Parkavi R ◽  
Priyanka C ◽  
Sujitha S. ◽  
Sheik Abdullah A
Keyword(s):  
Cloud Computing ◽  
Mobile Computing ◽  
Mobile Devices ◽  
Mobile Cloud Computing ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Mobile Service ◽  
Service Users ◽  
Security Issues ◽  
Mobile Computing Environment

Mobile Cloud Computing (MCC) which combines mobile computing and cloud computing, has become one of the industry ring words and a major conversation thread in the IT world with an explosive development of the mobile applications and emerging of cloud computing idea, the MCC has become a possible technology for the mobile service users. The concepts of Cloud computing are naturally meshed with mobile devices to allow on-the-go functionalities and benefits. The mobile cloud computing is emerging as one of the most important branches of cloud computing and it is expected to expand the mobile ecosystems. As more mobile devices enter the market and evolve, certainly security issues will grow as well. Also, enormous growth in the variety of devices connected to the Internet will further drive security needs. MCC provides a platform where mobile users make use of cloud services on mobile devices. The use of MCC minimizes the performance, compatibility, and lack of resources issues in mobile computing environment.

Assessing Security with Regard to Cloud Applications in STEM Education

2016 ◽  
pp. 260-276
Author(s):  
Ihssan Alkadi
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Stem Education ◽  
Personal Data ◽  
Cloud System ◽  
Password Authentication ◽  
Security Issues ◽  
Security Algorithm ◽  
Cloud Applications ◽  
And Storage

There are many steps involved with securing a cloud system and its applications (SaaS) and developed ones in (PaaS). Security and privacy issues represent the biggest concerns to moving services to external clouds (Public). With cloud computing, data are stored and delivered across the Internet. The owner of the data does not have control or even know where their data are being stored. Additionally, in a multi-tenant environment, it may be very difficult for a cloud service provider to provide the level of isolation and associated guarantees that are possible with an environment dedicated to a single customer. Unfortunately, to develop a security algorithm that outlines and maps out the enforcement of a security policy and procedure can be a daunting task. A good security algorithm presents a strategy to counter the vulnerabilities in a cloud system. This chapter covers the complete overview, comparative analysis of security methods in Cloud Applications in STEM Education and the introduction of a new methodology that will enforce cloud computing security against breaches and intrusions. Much light will be shed on existing methodologies of security on servers used for cloud applications in STEM education and storage of data, and several methods will be presented in addition to the newly developed method of security in cloud-based servers, such as the MIST (Alkadi). Not only can cloud networks be used to gather sensitive information on multiple platforms, also there are needs to prevent common attacks through weak password recovery, retrieval, authentication, and hardening systems; otherwise hackers will spread cyber mayhem. Discussion of current security issues and algorithms in a real world will be presented. Different technologies are being created and in constant competition to meet the demands of users who are generally “busy”. The selling point of these technologies is the ability to address these demands without adding more to any workloads. One of the demands often discussed is that users want to have their digital information accessible from anywhere at any time. This information includes documents, audio libraries, and more. Users also demand the ability to manage, edit and update this information regardless of physical location. Somewhat recently, mobile devices such as laptops, tablets, and smartphones have provided these abilities. This is no small feat as vendors and providers have reduced the size of these devices to increase mobility. However, as the amount of personal information that users are wanting to access has grown exponentially, manipulation and storage of it require more capable devices. To meet increased demands, increasing the capabilities of mobile devices may be impractical. Making mobile devices more powerful without technological advancement would require that the device be larger and use more resources such as battery life and processing power to function properly. Storing all of a user's information on a mobile device that travels everywhere also adds vulnerability risks. The best technical solution to having a user's information accessible is some sort of online storage where there is the convenience to store, manipulate and retrieve data. This is one of the most practical applications for the concept of cloud computing in STEM education. As storage capabilities and Internet bandwidth has increased, so has the amount of personal data that users store online. And today, the average user has billions of bytes of data online. Access is everywhere and whenever is needed. As everyone started doing so, people want their data safe and secure to maintain their privacy. As the user base grew in size, the number of security issues of the personal data started to become increasingly important. As soon as someone's data are in the remote server, unwanted users or “hackers” can have many opportunities to compromise the data. As the online server needs to be up and running all the time, the only way to secure the cloud server is by using better passwords by every user. By the same token, the flaws in the password authentication and protection system can also help unwanted users to get their way to other people's personal data. Thus, the password authentication system should also be free from any loopholes and vulnerabilities.

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