WITHDRAWN: A study on cloud computing challenges and its mitigations

Logesswari, S.; Jayanthi, S.; KalaiSelvi, D.; Muthusundari, S.; Aswin, V.

doi:10.1016/j.matpr.2020.10.655

Cited by 13 publications

(8 citation statements)

References 5 publications

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“…Although open-source clouds like OpenStack, Eucalyptus, OpenNebula, and CloudStack are more and more expanding, it is not easy to migrate to the cloud infrastructure, especially for critical services such as banking, and health. Cloud computing, however, is not without its challenges, these challenges include data protection and privacy issues, unequal availability of services, restricted compatibility with existing apps and systems, and some poor regulatory structures [4]. In respect of searching to mitigate these challenges, new architectures are proposed by researchers, hence the advent of ICCEs.…”

Section: Interconnected Cloud Computing Environmentmentioning

confidence: 99%

“…Platform as a service (PaaS) removes the need for companies to manage and develop conventional platforms to construct applications. Software as a service (SaaS) provides software hosting [4]. Cloud computing implement four models of deployment: i) public cloud, a multi-contributor framework that enables numerous tenants to share various web server resources; ii) private cloud, a single-contributor framework that allows the usage of cloud services by consumers; iii) hybrid cloud for private and public CSPs to share resources; and iv) federated cloud, in which numerous CSPs operate together under one authority [5].…”

Section: Introductionmentioning

confidence: 99%

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Monitoring and resource management taxonomy in interconnected cloud infrastructures: a survey

et al. 2022

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Cloud users have recently expanded dramatically. The cloud service providers (CSPs) have also increased and have therefore made their infrastructure more complex. The complex infrastructure needs to be distributed appropriately to various users. Also, the advances in cloud computing have led to the development of interconnected cloud computing environments (ICCEs). For instance, ICCEs include the cloud hybrid, intercloud, multi-cloud, and federated clouds. However, the sharing of resources is not facilitated by specific proprietary technologies and access interfaces used by CSPs. Several CSPs provide similar services but have different access patterns. Data from various CSPs must be obtained and processed by cloud users. To ensure that all ICCE tenants (users and CSPs) benefit from the best CSPs, efficient resource management was suggested. Besides, it is pertinent that cloud resources be monitored regularly. Cloud monitoring is a service that works as a third-party entity between customers and CSPs. This paper discusses a complete cloud monitoring survey in ICCE, focusing on cloud monitoring and its significance. Several current open-source monitoring solutions are discussed. A taxonomy is presented and analyzed for cloud resource management.

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Section: Interconnected Cloud Computing Environmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Monitoring and resource management taxonomy in interconnected cloud infrastructures: a survey

et al. 2022

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“…Here, eavesdropping on the data can help the attacker modify the message. In addition, message relays can also be altered by the attacker [95]. This type of attack intends to obtain sensitive information being yielded, and then the attack can occur during an ongoing communication if the channel of communication is also compromised [96].…”

Section: Man-in-the-middle Attacksmentioning

confidence: 99%

Cyber Security in IoT-Based Cloud Computing: A Comprehensive Survey

et al. 2021

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Cloud computing provides the flexible architecture where data and resources are dispersed at various locations and are accessible from various industrial environments. Cloud computing has changed the using, storing, and sharing of resources such as data, services, and applications for industrial applications. During the last decade, industries have rapidly switched to cloud computing for having more comprehensive access, reduced cost, and increased performance. In addition, significant improvement has been observed in the internet of things (IoT) with the integration of cloud computing. However, this rapid transition into the cloud raised various security issues and concerns. Traditional security solutions are not directly applicable and sometimes ineffective for cloud-based systems. Cloud platforms’ challenges and security concerns have been addressed during the last three years, despite the successive use and proliferation of multifaceted cyber weapons. The rapid evolution of deep learning (DL) in the artificial intelligence (AI) domain has brought many benefits that can be utilized to address industrial security issues in the cloud. The findings of the proposed research include the following: we present a comprehensive survey of enabling cloud-based IoT architecture, services, configurations, and security models; the classification of cloud security concerns in IoT into four major categories (data, network and service, applications, and people-related security issues), which are discussed in detail; we identify and inspect the latest advancements in cloud-based IoT attacks; we identify, discuss, and analyze significant security issues in each category and present the limitations from a general, artificial intelligence and deep learning perspective; we provide the technological challenges identified in the literature and then identify significant research gaps in the IoT-based cloud infrastructure to highlight future research directions to blend cybersecurity in cloud.

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“…In cloud environment, the user can access to the cloud services using a set of authentication methods that can determine the user identity. After verifying the user identity, a set of authorizations will be allowed for each user according to his privileges and level of control [1]. The cloud services will be provided for each user based on the user IP address, access level, and domain of data [2].…”

Section: Introductionmentioning

confidence: 99%

A Multi-Factor Authentication-Based Framework for Identity Management in Cloud Applications

Said¹,

Mostafa²,

Hassan³

et al. 2022

Computers, Materials &Amp; Continua

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User's data is considered as a vital asset of several organizations. Migrating data to the cloud computing is not an easy decision for any organization due to the privacy and security concerns. Service providers must ensure that both data and applications that will be stored on the cloud should be protected in a secure environment. The data stored on the public cloud will be vulnerable to outside and inside attacks. This paper provides interactive multi-layer authentication frameworks for securing user identities on the cloud. Different access control policies are applied for verifying users on the cloud. A security mechanism is applied to the cloud application that includes user registration, granting user privileges, and generating user authentication factor. An intrusion detection system is embedded to the security mechanism to detect malicious users. The multi factor authentication, intrusion detection, and access control techniques can be used for ensuring the identity of the user. Finally, encryption techniques are used for protecting the data from being disclosed. Experimental results are carried out to verify the accuracy and efficiency of the proposed frameworks and mechanism. The results recorded high detection rate with low false positive alarms.

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WITHDRAWN: A study on cloud computing challenges and its mitigations

Cited by 13 publications

References 5 publications

Monitoring and resource management taxonomy in interconnected cloud infrastructures: a survey

Monitoring and resource management taxonomy in interconnected cloud infrastructures: a survey

Cyber Security in IoT-Based Cloud Computing: A Comprehensive Survey

A Multi-Factor Authentication-Based Framework for Identity Management in Cloud Applications

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