28,287 research outputs found
Secure Cloud Storage with Client-Side Encryption Using a Trusted Execution Environment
With the evolution of computer systems, the amount of sensitive data to be
stored as well as the number of threats on these data grow up, making the data
confidentiality increasingly important to computer users. Currently, with
devices always connected to the Internet, the use of cloud data storage
services has become practical and common, allowing quick access to such data
wherever the user is. Such practicality brings with it a concern, precisely the
confidentiality of the data which is delivered to third parties for storage. In
the home environment, disk encryption tools have gained special attention from
users, being used on personal computers and also having native options in some
smartphone operating systems. The present work uses the data sealing, feature
provided by the Intel Software Guard Extensions (Intel SGX) technology, for
file encryption. A virtual file system is created in which applications can
store their data, keeping the security guarantees provided by the Intel SGX
technology, before send the data to a storage provider. This way, even if the
storage provider is compromised, the data are safe. To validate the proposal,
the Cryptomator software, which is a free client-side encryption tool for cloud
files, was integrated with an Intel SGX application (enclave) for data sealing.
The results demonstrate that the solution is feasible, in terms of performance
and security, and can be expanded and refined for practical use and integration
with cloud synchronization services
An Optimized Genetic Algorithm-Based Non-Commutative Encryption Method for Securing Data in the Cloud
This research introduces a novel non-commutative encryption approach designed to enhance data protection in the context of cloud computing. Leveraging the power of Optimized Genetic Algorithms (OGA), the proposed method aims to fortify the security of sensitive information by introducing non-commutative cryptographic techniques. Cloud computing, while offering unparalleled convenience and scalability, poses inherent security challenges, making robust encryption crucial for safeguarding user data. Through the use of a non-commutative encryption technique, this work presents a novel approach to Quantum Key Distribution (QKD). The integration of genetic algorithms serves to optimize the encryption process, ensuring a balance between computational efficiency and heightened security. There have been several data recovery procedures proposed by researchers, but none of them have shown to be dependable or useful. The suggested method allows users to access data from any backup server if the main cloud server becomes unreliable and cannot provide users with data. In this paper, they perform the analysis based on several parameters such as encryption time, decryption time, success rate, failure rate, throughput, and Avalanche effect. After comparing the proposed work with existing methods, the proposed method has low encryption (312ms)/decryption time (314ms), and a high success rate (100ms)/ failure rate (96ms)
Running Big Data Privacy Preservation in the Hybrid Cloud Platform
Now a day’s cloud computing has been used all over the industry, due to rapid growth in information technology and mobile device technology. It is more important task, user’s data privacy preservation in the cloud environment. Big data platform is collection of sensitive and non-sensitive data. To provide solution of big data security in the cloud environment, organization comes with hybrid cloud approach. There are many small scale industries arising and making business with other organization. Any organization data owner or customers never want to scan or expose their private data by the cloud service provider. To improve security performance, cloud uses data encryption technique on original data in public cloud. Proposed system work is carried out how to improve image data privacy preserving in hybrid cloud. For that we are implementing image encryption algorithm based on Rubik’s cube principle improves the image cryptography for the public cloud data securit
To Share or Not to Share in Client-Side Encrypted Clouds
With the advent of cloud computing, a number of cloud providers have arisen
to provide Storage-as-a-Service (SaaS) offerings to both regular consumers and
business organizations. SaaS (different than Software-as-a-Service in this
context) refers to an architectural model in which a cloud provider provides
digital storage on their own infrastructure. Three models exist amongst SaaS
providers for protecting the confidentiality data stored in the cloud: 1) no
encryption (data is stored in plain text), 2) server-side encryption (data is
encrypted once uploaded), and 3) client-side encryption (data is encrypted
prior to upload). This paper seeks to identify weaknesses in the third model,
as it claims to offer 100% user data confidentiality throughout all data
transactions (e.g., upload, download, sharing) through a combination of Network
Traffic Analysis, Source Code Decompilation, and Source Code Disassembly. The
weaknesses we uncovered primarily center around the fact that the cloud
providers we evaluated were each operating in a Certificate Authority capacity
to facilitate data sharing. In this capacity, they assume the role of both
certificate issuer and certificate authorizer as denoted in a Public-Key
Infrastructure (PKI) scheme - which gives them the ability to view user data
contradicting their claims of 100% data confidentiality. We have collated our
analysis and findings in this paper and explore some potential solutions to
address these weaknesses in these sharing methods. The solutions proposed are a
combination of best practices associated with the use of PKI and other
cryptographic primitives generally accepted for protecting the confidentiality
of shared information
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