scholarly journals Query-Biased Preview over Outsourced and Encrypted Data

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Ningduo Peng ◽  
Guangchun Luo ◽  
Ke Qin ◽  
Aiguo Chen
Keyword(s):  
Private Information ◽  
Cloud Storage ◽  
Communication Complexity ◽  
Third Party ◽  
Single Server ◽  
Sensitive Data ◽  
Encrypted Data ◽  
Cloud Storage Service ◽  
Dynamic Computation ◽  
Storage Complexity

For both convenience and security, more and more users encrypt their sensitive data before outsourcing it to a third party such as cloud storage service. However, searching for the desired documents becomes problematic since it is costly to download and decrypt each possibly needed document to check if it contains the desired content. An informative query-biased preview feature, as applied in modern search engine, could help the users to learn about the content without downloading the entire document. However, when the data are encrypted, securely extracting a keyword-in-context snippet from the data as a preview becomes a challenge. Based on private information retrieval protocol and the core concept of searchable encryption, we propose a single-server and two-round solution to securely obtain a query-biased snippet over the encrypted data from the server. We achieve this novel result by making a document (plaintext) previewable under any cryptosystem and constructing a secure index to support dynamic computation for a best matched snippet when queried by some keywords. For each document, the scheme hasO(d)storage complexity andO(log(d/s)+s+d/s)communication complexity, wheredis the document size andsis the snippet length.

A New User-controlled and Efficient Encrypted Data Sharing Model in Cloud Storage

2019 ◽  
Vol 13 (4) ◽  
pp. 356-363
Author(s):  
Yuezhong Wu ◽  
Wei Chen ◽  
Shuhong Chen ◽  
Guojun Wang ◽  
Changyun Li
Keyword(s):  
Data Sharing ◽  
Data Security ◽  
Cloud Storage ◽  
Screening Program ◽  
Original Data ◽  
Third Party ◽  
Active System ◽  
Encrypted Data ◽  
Active User ◽  
User Data

Background: Cloud storage is generally used to provide on-demand services with sufficient scalability in an efficient network environment, and various encryption algorithms are typically applied to protect the data in the cloud. However, it is non-trivial to obtain the original data after encryption and efficient methods are needed to access the original data. Methods: In this paper, we propose a new user-controlled and efficient encrypted data sharing model in cloud storage. It preprocesses user data to ensure the confidentiality and integrity based on triple encryption scheme of CP-ABE ciphertext access control mechanism and integrity verification. Moreover, it adopts secondary screening program to achieve efficient ciphertext retrieval by using distributed Lucene technology and fine-grained decision tree. In this way, when a trustworthy third party is introduced, the security and reliability of data sharing can be guaranteed. To provide data security and efficient retrieval, we also combine active user with active system. Results: Experimental results show that the proposed model can ensure data security in cloud storage services platform as well as enhance the operational performance of data sharing. Conclusion: The proposed security sharing mechanism works well in an actual cloud storage environment.

scholarly journals Privacy Preserving Analytics in Outsourced Healthcare System

2020 ◽  
Vol 9 (9) ◽  
pp. 329-333
Keyword(s):  
Healthcare System ◽  
Cloud Storage ◽  
Learning Algorithm ◽  
Homomorphic Encryption ◽  
Digital Health ◽  
Health Data ◽  
Third Party ◽  
Sensitive Data ◽  
Data Intensive ◽  
Cloud Server

The most data intensive industry today is the healthcare system. The advancement in technology has revolutionized the traditional healthcare practices and led to enhanced E-Healthcare System. Modern healthcare systems generate voluminous amount of digital health data. These E-Health data are shared between patients and among groups of physicians and medical technicians for processing. Due to the demand for continuous availability and handling of these massive E-Health data, mostly these data are outsourced to cloud storage. Being cloud-based computing, the sensitive patient data is stored in a third-party server where data analytics are performed, hence more concern about security raises. This paper proposes a secure analytics system which preserves the privacy of patients’ data. In this system, before outsourcing, the data are encrypted using Paillier homomorphic encryption which allows computations to be performed over encrypted dataset. Then Decision Tree Machine Learning algorithm is used over this encrypted dataset to build the classifier model. This encrypted model is outsourced to cloud server and the predictions about patient’s health status is displayed to the user on request. In this system nowhere the data is decrypted throughout the process which ensures the privacy of patients’ sensitive data.

scholarly journals A Cloud Based Secure Voting System using Homomorphic Encryption for Android Platform

2016 ◽  
Vol 6 (6) ◽  
pp. 2994
Author(s):  
Manish Ranjan ◽  
Ayub Hussain Mondal ◽  
Monjul Saikia
Keyword(s):  
Service Provider ◽  
Cloud Storage ◽  
Homomorphic Encryption ◽  
Information Leakage ◽  
Third Party ◽  
Sensitive Information ◽  
Cipher Text ◽  
Cloud Storage Service ◽  
Android Platform ◽  
Voting System

<p>Cloud based service provider are at its top of its services for various applications, as their services are very much reachable from anywhere anytime in current days. It is responsibility of the company that the Cloud storage is owned and maintained by themselves keeping the data available and accessible, and the physical environment protected and running. Could storage provider seem to be uncertain of confidentiality in many cases, as we need to limit ourselves on trust to a third party. Keeping our sensitive data ready to access any time anywhere with preventing any information leakage is a challenging task. Cryptography in this scenario plays an important role, providing security for information to protect valuable information resources on intranets, Internet and the cloud. In addition, Homomorphic cryptosystem is a form of Cryptography where some specific computation can be performed over the cipher text producing a resultant cipher text which, when decrypted, equals the result of operations carry out on the plaintext. With help of this unique property of homomorphism cryptography we proposed a system to keep sensitive information in encrypted form in the cloud storage/service provider and used those data as whenever we require. The scheme proposed here is designed for a secure online voting system on Android platform and voted information is encrypted and stored those in the cloud.</p>

scholarly journals IMPLEMENTATION OF PRIVACY PRESERVING AND DYNAMIC SEARCHING MECHANISM WITH BIOMETRIC AUTHENTICATION IN CLOUD STORAGE

2021 ◽  
Vol 9 (2) ◽  
pp. 894-912
Author(s):  
Sarita Motghare, Et. al.
Keyword(s):  
Private Information ◽  
Cloud Storage ◽  
User Authentication ◽  
Third Party ◽  
Mining Operations ◽  
Search System ◽  
Data Set ◽  
External Data ◽  
Main Challenge ◽  
Better Than

In the recent times, cloud storage tends to be a primary storage means for external data. Cloud defense of the data against attacks is the main challenge. Private or semi-private information growth has rapidly expanded over the information network; privacy safeguards have failed to address the search mechanisms. In the field of information networks, privacy protection is an important factor in carrying out various data mining operations with encrypted data stored in different storage systems. A tolerance and protection against data corruption mechanism should be developed which is difficult to achieve. Furthermore, as there is no adequate audit mechanism, the integrity of the stored data become questionable. In addition to this, the user authentication is another challenge. The current solution provides only a remote audit mechanism. It requires data owners to always remain online so that the auditing process is manually handled, which is sometimes unworkable. In this paper, we propose a new, regenerative, public audit methodology accompanied by third-party audits. The existing data search system provides one solution that can be used to maintain the confidentiality of indexing. Documents are stored on a private server in plain word form, which compromise the protection of privacy. So that this system is improved to make the document more secure and efficient, we first store the documents in encrypted form on server, and use the Key Distribution Center (KDC). To generate keys the KDC uses the user's biometric feature. In order to improve the search experience, we also implement TF-IDF, which provides an efficient evaluation of the results. Lastly, we carry out comprehensive data set experiments to evaluate our proposed system performance. Experimental results demonstrate that in terms of safeguarding the privacy, efficient and safe search for encrypted distributed documents the proposed system is better than existing. The methodology suggested also includes an auditing mechanism by third parties to ensure data integrity.

Attributes Based Storage System for Secure De-Duplication of Encrypt Data in Cloud

2020 ◽  
Vol 17 (4) ◽  
pp. 1937-1942
Author(s):  
S. Sivasankari ◽  
V. Lavanya ◽  
G. Saranya ◽  
S. Lavanya
Keyword(s):  
Cloud Storage ◽  
Storage System ◽  
Third Party ◽  
Encrypted Data ◽  
Storage Cost ◽  
Multiple Data ◽  
Outsourced Data ◽  
Data Owner ◽  
Encrypt Data ◽  
Cloud Server

These days, Cloud storage is gaining importance among individual and institutional users. Individual and foundations looks for cloud server as a capacity medium to diminish their capacity load under nearby devices. In such storage services, it is necessary to avoid duplicate content/repetitive storage of same data to be avoided. By reducing the duplicate content in cloud storage reduces storage cost. De-duplication is necessary when multiple data owner outsource the same data, issues related to security and ownership to be considered. As the cloud server is always considered to be non trusted, as it is maintained by third party, thus the data stored in cloud is always encrypted and uploaded, thus randomization property of encryption affects de-duplication. It is necessary to propose a serverside de-duplication scheme for handling encrypted data. The proposed scheme allows the cloud server to control access to outsourced data even when the ownership changes dynamically.

scholarly journals An efficient secure Internet of things data storage auditing protocol with adjustable parameter in cloud computing

2017 ◽  
Vol 13 (1) ◽  
pp. 155014771668657 ◽  
Author(s):  
Meng Liu ◽  
Xuan Wang ◽  
Chi Yang ◽  
Zoe Lin Jiang ◽  
Ye Li
Keyword(s):  
Internet Of Things ◽  
Data Storage ◽  
Cloud Storage ◽  
Cost Effective ◽  
Optimal Number ◽  
Third Party ◽  
Cloud Systems ◽  
Cloud Storage Service ◽  
Pairing Based Cryptography ◽  
Cloud Users

Nowadays, an increasing number of cloud users including both individuals and enterprises store their Internet of things data in cloud for benefits like cost saving. However, the cloud storage service is often regarded to be untrusted due to their loss of direct control over the data. Hence, it is necessary to verify the integrity of their data on cloud storage servers via a third party. In real cloud systems, it is very important to improve the performance of the auditing protocol. Hence, the well-designed and cost-effective auditing protocol is expected to meet with the performance requirement while the data size is very large in real cloud systems. In this article, we also propose an auditing protocol based on pairing-based cryptography, which can reduce the computation cost compared to the state-of-the-art third-party auditing protocol. Moreover, we also study how to determine the number of sectors to achieve the optimal performance of our auditing protocol in a case of the same challenged data. And an equation for computing the optimal number of sectors is proposed to further improve the performance of our auditing protocol. Both the mathematical analysis method and experiment results show that our solution is more efficient.

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.

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