Major Vulnerabilities and Their Prevention Methods in Cloud Computing

John, Jomina; Norman, Jasmine

doi:10.1007/978-981-13-1882-5_2

Cited by 17 publications

(5 citation statements)

References 21 publications

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“…However, V-BOINC have been modified to allow customized data flow among the server. For instance, for upgrading the server on the VM status, BOINC enables client-server connection through sending XML messages that were interpreted locally by the received object; the host's information is transmitted to the server [ 63 ]. The authenticator identifies the (Host, BOINC version and Platform Type), the V-BOINC was restricted from consuming no more than the accessibility of 90% from the memory by the volunteer users, which provided in the volunteer host idle state.…”

Section: Proposed Modelmentioning

confidence: 99%

A deep learning based steganography integration framework for ad-hoc cloud computing data security augmentation using the V-BOINC system

et al. 2022

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In the early days of digital transformation, the automation, scalability, and availability of cloud computing made a big difference for business. Nonetheless, significant concerns have been raised regarding the security and privacy levels that cloud systems can provide, as enterprises have accelerated their cloud migration journeys in an effort to provide a remote working environment for their employees, primarily in light of the COVID-19 outbreak. The goal of this study is to come up with a way to improve steganography in ad hoc cloud systems by using deep learning. This research implementation is separated into two sections. In Phase 1, the “Ad-hoc Cloud System” idea and deployment plan were set up with the help of V-BOINC. In Phase 2, a modified form of steganography and deep learning were used to study the security of data transmission in ad-hoc cloud networks. In the majority of prior studies, attempts to employ deep learning models to augment or replace data-hiding systems did not achieve a high success rate. The implemented model inserts data images through colored images in the developed ad hoc cloud system. A systematic steganography model conceals from statistics lower message detection rates. Additionally, it may be necessary to incorporate small images beneath huge cover images. The implemented ad-hoc system outperformed Amazon AC2 in terms of performance, while the execution of the proposed deep steganography approach gave a high rate of evaluation for concealing both data and images when evaluated against several attacks in an ad-hoc cloud system environment.

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Section: Proposed Modelmentioning

confidence: 99%

A deep learning based steganography integration framework for ad-hoc cloud computing data security augmentation using the V-BOINC system

et al. 2022

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“…The primary objective of the author in [10] is to define a consistent taxonomy for security needs, threats, vulnerabilities, and responses in order to carry out the suggested end-to-end mapping. Using an agent-based model, provides a methodology for identifying cyber security threats in the construction sector and analyses the vulnerability of traditional and hybrid delivery methods (ABM).…”

Section: Related Workmentioning

confidence: 99%

Investigation of Cloud Computing Security Issues & Challenges

Sharma¹,

Singh²

2021

Atlantis Highlights in Computer Sciences

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The Trends of using cloud computing in IT industries is increasing since the Inception of this innovative technology. This new shift in the industrial technology, which will grow and develop continuously their e-governance in the coming few years. Most of the enterprises are migrating towards the cloud-computing environment rapidly due to its various advantages over traditional one. As per cisco, more than 93% workloads will be processed by Cloud data centers in 2021. Even several republics have already initiated to shape their own governmental public cloud around the globe. Phishing attempts affected the majority of educational establishments (60 percent) and account compromise (33 percent) in 2020. According to Gartner, consumers are responsible for more than 95 percent of cloud security flaws. Increasing frequent cyber-attacks potentially cause significant material damage if no special security measures are taken. The objective here is to investigate the security issues & challenges in terms of cloud specific vulnerabilities & threats using real time experimental setup with vulnerability scanner which further provide an ease to applications deployment.

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“…Since a majority of the medical data and patient information is highly sensitive and confidential, it is treacherous to depend on third party centralized servers for storage. Third party entities increase the security risks and can lead to attacks such as denial of service (DoS) or distributed denial of service (DDoS) attacks (John and Norman, 2019) and ransomware attacks, which have greater potential to breach the security protocols (Thamer & Alubady, 2021;Gopinath and Olmsted, 2022). Considering the susceptibility of medical data and patient information, it is crucial to secure the data by implementing a robust and efficient technique which can securely store and share the data across multiple stakeholders (Singh et al, 2021;Hathaliya & Tanwar, 2020;Awotunde et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Blockchain-Based Framework for Privacy Preservation and Securing EHR with Patient-Centric Access Control

Puneeth,

Parthasarathy

2024

AIP

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The technological advancements in the field of E-healthcare have resulted in unprecedented generation of medical data which increases the risk of data security and privacy. Ensuring the privacy of Electronic Health Records (EHR) has become challenging due to outsourcing of healthcare information in the cloud. This increases the chance of data leakage to unauthorized users and affects the privacy and integrity of the user data. It requires a trustworthy central authority to protect the sensitive patient information from both internal and external attacks. This paper presents a blockchain based privacy preservation framework for securing EHR data. The proposed framework integrates the immutability and decentralized nature of blockchain with advanced cryptographic techniques to ensure the confidentiality, integrity and availability of EHR. The EHR data are stored in an InterPlanetary File System (IPFS) which is encrypted using a hybrid cryptographic algorithm. In addition, a novel smart contact based patient-centric access control is designed in this paper using a blockchain-based SHA-256 hashing algorithm to protect the privacy of patient data. The experimental results show that the proposed framework enables secure sharing of health information between network users with improved data privacy and security. Furthermore, the optimized search process reduces the time and space complexity compared to the traditional search process. Through the utilization of smart contracts, this framework enforces patient-centric access controls and allows patients to manage and authorize access to their medical data.

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Major Vulnerabilities and Their Prevention Methods in Cloud Computing

Cited by 17 publications

References 21 publications

A deep learning based steganography integration framework for ad-hoc cloud computing data security augmentation using the V-BOINC system

A deep learning based steganography integration framework for ad-hoc cloud computing data security augmentation using the V-BOINC system

Investigation of Cloud Computing Security Issues & Challenges

Blockchain-Based Framework for Privacy Preservation and Securing EHR with Patient-Centric Access Control

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