WITHDRAWN: Internet cross-border service model based on 5G environment and cloud computing data platform

Wangfi, Shuwen; Wang, Wenying; Yu, Tan

doi:10.1016/j.micpro.2020.103520

Cited by 9 publications

(5 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One criticalfavored view of clouds is that scholars are not obliged to collect expensive computer infrastructures to perform studies or even install many software items. An ordinary scholar can conduct tests by allocating the critical cloud services [30].…”

Section: Background To the E-commerce Systemsmentioning

confidence: 99%

Cloud Computing based E-commerce Management Ontransaction Security Concepts

Chi

Sui

Alazab

et al. 2021

Preprint

View full text Add to dashboard Cite

The way e-commerce companies do commerce is transformed by cloud computing. Although the usage of cloud technology in e-commerce has grown suddenly, the advantages of cloud services platforms have not yet been exploited, especially for e-commerce applications. For decision-makers, it is vital that the optimized cloud-based computing solution like software as a service (SaaS), platform as a service (PaaS), or infrastructure as a service(IaaS) model is adopted as a multi-criteria decision-making (MCDM) issue and is thus dependent on a trustworthy and secured online shop. A new Cloud computing-based E-Commerce Management (CCECM) approach is provided to tackle the MCDM issue, a multiple-criteria group approach based on an ordering preference strategy by an idealized solution,and relying on the structure for a list of requirements. A small-to-medium firm uses the suggested system to ease the assessment and decision-making of the aspects connected with cloud e-commerce with security.The results show that small and moderate-sized e-commerce companies have higher secured and efficient communication. SaaS is asuitable alternative for difficulty, dependability, safety and protection, organizational preparedness, and corporate size. At the same time, adaptability and scaling can be enhanced in the choosing of PaaS or IaaS.

show abstract

Section: Background To the E-commerce Systemsmentioning

confidence: 99%

Cloud Computing based E-commerce Management Ontransaction Security Concepts

Chi

Sui

Alazab

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Cloud computing is an information technolofy (IT) model enabling to provide on-demand access with rapid elasticity to a shared pool of computing resources. It offers several benefits to individual users and organizations in terms of reducing capital expenditure required to build IT infrastructure and avoiding the operational expenditure spent in maintaining the IT infrastructure [1]. These benefits have opened business avenue for new budding entrepreneur as well have encouraged many organizations across the globe to migrate their business activities to cloud and witness remarkable growth with essential characteristics of cloud such as higher availability, geographic reach, and business continuity [2], [3].…”

Section: Introductionmentioning

confidence: 99%

Deep self-taught learning framework for intrusion detection in cloud computing environment

Vaiyapuri,

Binbusayyis

2024

IJ-AI

View full text Add to dashboard Cite

<p>Cloud has become a target-rich environment for malicious attacks by cyber intruders. Security is a major concern and remains an obstacle to the adoption of cloud computing. The intrusion detection system (IDS) is regarded as defense-in-depth. Unfortunately, most machine learning approaches designed for cloud intrusion detection require large amounts of labeled attack samples, but in real practice, they are limited. Therefore, the key impetus of this work is to introduce self-taught learning (STL) combining stacked sparse autoencoder (SSAE) with long short-term memory (LSTM) as a candidate solution to learn the robust feature representation and efficiently improve the performance of IDS with respect to false alarm rate (FAR) and detection rate (DR). Accordingly, the proposed approach as a first step employs SSAE to achieve dimensional reduction by learning the discriminative features from network traffic. The approach adopts LSTM to recognize the intrusion with the features encoded by SSAE. To evaluate the detective performance of our model, a comprehensive set of experiments are conducted on NSL-KDD. Also, ablation experiments are conducted to show the contribution of each component of our approach. Further, the comparative analysis shows the efficacy of our approach against the existing approaches with an accuracy of 86.31%.</p>

show abstract

“…Computing offloading shortens the processing time by offloading some or all computing tasks to the edge server instead of the cloud server, which is an effective means to solve the problem of the insufficient computing power of mobile terminal devices and prolong the use time. How to realise collaborative computing between mobile terminal devices and edge servers is a hot issue in current research ( Wangfi, Wang & Tan, 2020 ). Moreover, how to survive in the turbulent market environment, maintain the stability of the supply chain and comprehensively use CBE service capabilities and other means to meet customers’ needs, seek long-term development, and improve the operational performance of the supply chain has become the focus of CBE supply chain enterprises.…”

Section: Introductionmentioning

confidence: 99%

Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing

Dong¹,

Chen²,

Wang³

2023

PeerJ Computer Science

View full text Add to dashboard Cite

The cross-border e-commerce supply chain network (CBESCN) has extensive geographical coverage, trade barriers and complexity of cross-border logistics issues, which makes its construction and development face many challenges. This article focuses on solving the operation optimisation problem of CBESCN under the background of the Internet of Things. A genetic algorithm constructed and solved the resource scheduling model of the supply chain of e-commerce enterprises in international trade. In addition, the mobile edge computing (MEC) optimisation scheme based on partial computation unloading is involved. The initial offload ratio is set and supply chain resources are allocated, then the remaining computing resources are distributed according to the server’s computing power. Finally, the offload is optimised according to the resource allocation. The experimental results show that time delay and cost adjustment strategies can improve the CBE supply chain’s comprehensive ability. The supply chain optimisation scheme proposed in this article can effectively use supply chain resources according to the requirements of computing tasks to reduce the total delay of task execution and the consumption of node computing.

show abstract

WITHDRAWN: Internet cross-border service model based on 5G environment and cloud computing data platform

Cited by 9 publications

References 8 publications

Cloud Computing based E-commerce Management Ontransaction Security Concepts

Cloud Computing based E-commerce Management Ontransaction Security Concepts

Deep self-taught learning framework for intrusion detection in cloud computing environment

Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing

Contact Info

Product

Resources

About