Integrity and Confidentiality in Cloud Outsourced Data

Rady, Mai; Abdelkader, Tamer; Ismail, Rasha M.

doi:10.1016/j.asej.2019.03.002

Cited by 35 publications

(15 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A recently published work [52] introduces a new cloud service, namely ''database as a service'' (DBaaS), where a service provider has responsibility to grant access of software, hardware, and network to users. It would enable them to access and manage a database.…”

Section: A Security Threats and Risk Mitigation Strategies (Rq1)mentioning

confidence: 99%

A Systematic Literature Review on Cloud Computing Security: Threats and Mitigation Strategies

et al. 2021

View full text Add to dashboard Cite

Cloud computing has become a widely exploited research area in academia and industry. Cloud computing benefits both cloud services providers (CSPs) and consumers. The security challenges associated with cloud computing have been widely studied in the literature. This systematic literature review (SLR) is aimed to review the existing research studies on cloud computing security, threats, and challenges. This SLR examined the research studies published between 2010 and 2020 within the popular digital libraries. We selected 80 papers after a meticulous screening of published works to answer the proposed research questions. The outcomes of this SLR reported seven major security threats to cloud computing services. The results showed that data tampering and leakage were among the highly discussed topics in the chosen literature. Other identified security risks were associated with the data intrusion and data storage in the cloud computing environment. This SLR's results also indicated that consumers' data outsourcing remains a challenge for both CSPs and cloud users. Our survey paper identified the blockchain as a partnering technology to alleviate security concerns. The SLR findings reveal some suggestions to be carried out in future works to bring data confidentiality, data integrity, and availability.

show abstract

Section: A Security Threats and Risk Mitigation Strategies (Rq1)mentioning

confidence: 99%

A Systematic Literature Review on Cloud Computing Security: Threats and Mitigation Strategies

et al. 2021

View full text Add to dashboard Cite

show abstract

“…The authors also proposed a method for storing data in a safe manner utilizing metadata. The authors of [12] compared several cryptographic algorithms, cryptographic data structures, Hash processes, digital signatures, and other cryptographic methods. Finally, the suggested architecture ensures data availability, confidentiality, privacy, and availability, among other things.…”

Section: Literature Surveymentioning

confidence: 99%

A novel data classification-based scheme for cloud data security using various cryptographic algorithms

Haq

Kumar

2022

IRASE

View full text Add to dashboard Cite

Digital technologies had an effect on people's lives. The majority of these digital devices rely on cloud storage to meet their memory needs. Hundreds of thousands of images, videos, and audio files are being transferred to cloud storage. Thousands of people around the world access these media every second. Unauthorized access to these media must be avoided. One of the weak points for data breaches is the user-end encryption. This paper suggests a strategy for improving cloud data protection by combining the AES and blowfish encryption and decryption algorithms. AES-256 is used as the first layer, followed by blowfish as the second layer, in the hybrid solution. The output of the first layer is input to the second layer and the final result is analyzed. The proposed method also discusses other combined approaches such as AES with other traditional algorithms but the proposed method gives significant results compared to other approaches.

show abstract

“…ey [27] also proposed a privacypreserving outsourced calculation toolkit, which allows data owners to securely outsource their data to the cloud for storage and calculation. Rady et al [28] designed a new architecture that achieves the confidentiality and integrity of query results of the outsourced database. Yu et al [29] devised a verifiable outsourced computation scheme over encrypted data by employing fully homomorphic encryption and polynomial factorization algorithm.…”

Section: E Other Work On Privacy Preservation For Machinementioning

confidence: 99%

Distributed Outsourced Privacy-Preserving Gradient Descent Methods among Multiple Parties

Tan

Zhang

et al. 2021

Security and Communication Networks

View full text Add to dashboard Cite

The Internet of Things (IoT) is one of the latest internet evolutions. Cloud computing is an important technique which realizes the computational demand of largely distributed IoT devices/sensors by employing various machine learning models. Gradient descent methods are widely employed to find the optimal coefficients of a machine learning model in the cloud computing. Commonly, the data are distributed among multiple data owners, whereas the target function is held by the model owner. The model owner can train its model over data owner’s data and provide predictions. However, the dataset or the target function’s confidentiality may not be kept in secret during computations. Thus, security threats and privacy risks arise. To address the data and model’s privacy mentioned above, we present two new outsourced privacy-preserving gradient descent (OPPGD) method schemes over horizontally or vertically partitioned data among multiple parties, respectively. Compared to previously proposed solutions, our methods improve in comprehensiveness in a more general scene. The data privacy and the model privacy are preserved during the whole learning and prediction procedures. In addition, the execution performance evaluation demonstrates that our schemes can help the model owner to optimize its target function and provide exact prediction with high efficiency and accuracy.

show abstract

Integrity and Confidentiality in Cloud Outsourced Data

Cited by 35 publications

References 19 publications

A Systematic Literature Review on Cloud Computing Security: Threats and Mitigation Strategies

A Systematic Literature Review on Cloud Computing Security: Threats and Mitigation Strategies

A novel data classification-based scheme for cloud data security using various cryptographic algorithms

Distributed Outsourced Privacy-Preserving Gradient Descent Methods among Multiple Parties

Contact Info

Product

Resources

About