Evidence map›Paper›PMID 35712069›Full record

SynthesisComputational intelligence and neuroscience2022

The Rise of Cloud Computing: Data Protection, Privacy, and Open Research Challenges-A Systematic Literature Review (SLR).

Junaid Hassan, Danish Shehzad, Usman Habib, Muhammad Umar Aftab, Muhammad Ahmad, Ramil Kuleev, Manuel Mazzara

RetractedAbstract readSystematic ReviewRetracted Publication
In one paragraph

Synthesis in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Junaid HassanDepartment of Computer Science, National University of Computer and Emerging Sciences, Islamabad, Chiniot-Faisalabad Campus, Chiniot 35400, Pakistan.ORCID https://orcid.org/0000-0001-9770-9275
Danish ShehzadDepartment of Computer Science, Superior University, Lahore 54000, Pakistan.ORCID https://orcid.org/0000-0002-4767-3443
Usman HabibFaculty of Computer Sciences and Engineering, GIK Institute of Engineering Sciences and Technology, Topi, Swabi 23640, Khyber Pakhtunkhwa, Pakistan.
Muhammad Umar AftabDepartment of Computer Science, National University of Computer and Emerging Sciences, Islamabad, Chiniot-Faisalabad Campus, Chiniot 35400, Pakistan.ORCID https://orcid.org/0000-0002-9649-7757
Muhammad AhmadDepartment of Computer Science, National University of Computer and Emerging Sciences, Islamabad, Chiniot-Faisalabad Campus, Chiniot 35400, Pakistan.ORCID https://orcid.org/0000-0002-3320-2261
Ramil KuleevInstitute of Software Development and Engineering, Innopolis University, Innopolis 420500, Russia.ORCID https://orcid.org/0000-0001-5323-9515
Manuel MazzaraInstitute of Software Development and Engineering, Innopolis University, Innopolis 420500, Russia.ORCID https://orcid.org/0000-0002-3860-4948

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cloud computing is a long-standing dream of computing as a utility, where users can store their data remotely in the cloud to enjoy on-demand services and high-quality applications from a shared pool of configurable computing resources. Thus, the privacy and security of data are of utmost importance to all of its users regardless of the nature of the data being stored. In cloud computing environments, it is especially critical because data is stored in various locations, even around the world, and users do not have any physical access to their sensitive data. Therefore, we need certain data protection techniques to protect the sensitive data that is outsourced over the cloud. In this paper, we conduct a systematic literature review (SLR) to illustrate all the data protection techniques that protect sensitive data outsourced over cloud storage. Therefore, the main objective of this research is to synthesize, classify, and identify important studies in the field of study. Accordingly, an evidence-based approach is used in this study. Preliminary results are based on answers to four research questions. Out of 493 research articles, 52 studies were selected. 52 papers use different data protection techniques, which can be divided into two main categories, namely noncryptographic techniques and cryptographic techniques. Noncryptographic techniques consist of data splitting, data anonymization, and steganographic techniques, whereas cryptographic techniques consist of encryption, searchable encryption, homomorphic encryption, and signcryption. In this work, we compare all of these techniques in terms of data protection accuracy, overhead, and operations on masked data. Finally, we discuss the future research challenges facing the implementation of these techniques.

Indexed as

Cloud ComputingPrivacyComputer SecurityConfidentialityDelivery of Health Care

Identifiers

PMID35712069
PMCPMC9197654

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.