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A Systematic Literature Review on Continuous Integration and Deployment (CI/CD) for Secure cloud computing 20

A Systematic Literature Review on Continuous Integration and...

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20th international conference on Web Information Systems and Technologies, WEBIST 2024

作者： Saleh, Sabbir M. Madhavji, Nazim Steinbacher, John Department of Computer Science University of Western Ontario LondonON Canada IBM Canada Lab MarkhamON Canada

ISBN: (纸本)9789897587184

As cloud environments become widespread, cybersecurity has emerged as a top priority across areas such as networks, communication, data privacy, response times, and availability. Various sectors, including industries, healthcare, and government, have recently faced cyberattacks targeting their computing systems. Ensuring secure app deployment in cloud environments requires substantial effort. With the growing interest in cloud security, conducting a systematic literature review (SLR) is critical to identifying research gaps. Continuous Software engineering, which includes continuous integration (CI), delivery (CDE), and deployment (CD), is essential for software development and deployment. In our SLR, we reviewed 66 papers, summarising tools, approaches, and challenges related to the security of CI/CD in the cloud. We addressed key aspects of cloud security and CI/CD and reported on tools such as Harbor, SonarQube, and GitHub Actions. Challenges such as image manipulation, unauthorised access, and weak authentication were highlighted. The review also uncovered research gaps in how tools and practices address these security issues in CI/CD pipelines, revealing a need for further study to improve cloud-based security solutions. Copyright © 2024 by SCITEPRESS.

关键词： cloud security

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A Robust Fuzzy Based Multi-Keyword Similarity Search Model on cloud computing Platform Using Cipher Data Security Principles

A Robust Fuzzy Based Multi-Keyword Similarity Search Model o...

引用

2024 international conference on Innovative computing, Intelligent communication and Smart Electrical Systems, ICSES 2024

作者： Ramachandran, T.P. Shalini, K. Ranjith, S. Tejaswi, L.Lakshmi Bonde, Ajay Abbas, Nidal Deptof Ece Chennai India Qis College of Engineering and Technology Department of S&h Pondur Road Vengamukkapalem Ongole Prakasam India AndhraPradesh PrakasamDistrict523272 India Jeppiaar Engineering College Department of Ece Rajiv Gandhi salai Chennai119 India Qis College of Engineering and Technology Department of Mca Pondur Road Vengamukkapalem Ongole Prakasam AndhraPradesh PrakasamDistrict523272 India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Zarqa university Faculty of Economics and Administrative Sciences Department of Economic Zarqa Jordan College of Business Administration University of Business and Technology Jeddah21448 Saudi Arabia

ISBN: (纸本)9798331543617

In the era of cloud computing, secure data storage and retrieval have emerged as critical challenges due to the need to protect sensitive information while maintaining efficient access. This paper presents a robust fuzzy-based multi-keyword similarity search model that operates on encrypted cloud data, enhancing both security and performance. By combining fuzzy logic, homomorphic encryption, and multi-keyword search, this model offers improved accuracy in retrieving relevant documents based on user queries. The model achieves a search accuracy of 85% with two keywords, which increases progressively to 96.5% when 11 keywords are used. Additionally, the system demonstrates low encryption overhead, with encryption time scaling linearly as data size increases. The search time also remains efficient, growing from 50 ms for two keywords to 400 ms for 11 keywords. The model further enhances query efficiency, achieving 96% efficiency after processing 500 queries. The proposed solution addresses the growing need for secure and efficient cloud storage systems while ensuring user privacy. The results indicate the model's scalability, making it suitable for large datasets and high-volume cloud environments. © 2024 IEEE.

关键词： cloud security

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Autonomous target detection system based on embedded platform and cloud computing 3

Autonomous target detection system based on embedded platfor...

引用

3rd international conference on Machine Vision, Automatic Identification, and Detection, MVAID 2024

作者： Su, Linxia Zhou, Hanyan Li, Xinyue Cai, Yuan Department of Information and Communication Guilin University of Electronic Science and Technology Guangxi Guilin China

ISBN: (纸本)9781510681880

In today 's society, target detection technology, as a basic technology, has been widely used in many fields such as municipal, public security, medical, transportation, exploration and so on. However, there are many problems in the embedded target detection system currently on the market, such as cumbersome model training and retraining process, simple human-machine interface and difficult operation. In view of the above problems, this paper proposes an autonomous target detection system based on embedded platform and cloud computing. It mainly uses Raspberry Pi and USB camera to collect image data, and then transmits it to the cloud server through the network. It completes data annotation, model training and autonomous iterative training of the model in the cloud on the Web management platform. Through the cooperation of software and hardware, the target detection results can be viewed on the platform in real time, which realizes the visualization, automation and simplification of the target detection process are realized, and the operation difficulty of the system is reduced. © 2024 SPIE.

关键词： cloud platforms

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5G Spectrum Research 10

5G Spectrum Research

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10th IEEE international conference on Cyber Security and cloud computing and 9th IEEE international conference on Edge computing and Scalable cloud, CScloud-EdgeCom 2023

作者： Zhu, Peiyuan Xiao, Lijun Tan, Shu Cai, Jiahong Huo, Yingzi Zhang, Ronglin Universiti Utara Malaysia UUM COB Postgraduate Studies Unit Kuala Lumpur Malaysia Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan411201 China

ISBN: (纸本)9798350312461

With the growing demand for communication and the rapid development of global mobile communication technology, the fourth generation of mobile communication can no longer meet the needs of people in their working lives for mobile network communication, and the fifth generation of mobile communication is born. This paper first introduces three strategies for the use of the 5G spectrum, namely spectrum dedication, spectrum re-farming, and spectrum sharing. Secondly, it introduces the three main application scenarios for the 5G spectrum, namely enhanced mobile broadband (eMBB), ultrahigh reliability and ultra-low latency services (URLLC), and massive IoT communications (MTC). The presentation concludes with a summary of the impact of the 5G spectrum in today's society and an outlook on its future development. © 2023 IEEE.

关键词： 5G mobile communication systems

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Design and Realization of Electrical Power Management System Based on Secure Transport 24

Design and Realization of Electrical Power Management System...

引用

6th international conference on Telecommunications and communication engineering

作者： Lin, Jie Qin, JingTao Sichuan Railway Coll Chengdu Sichuan Peoples R China Chengdu Univ Informat Technol Coll Commun Engn Chengdu Sichuan Peoples R China

ISBN: (纸本)9798400709630

with the development of science and technology, new application scenarios have new demands for power distribution management system. The purpose of the research is to use the Internet of'Ihings technology and cloud computing technology to achieve distribution information collection and remote distribution management, real-time monitoring of the power system, and reasonable distribution of power resources. Through the analysis and research of the overall system design, key technology realization, practical testing and other aspects, the power distribution management service is provided in the technology-driven mode, which solves the security problems in the data transmission process and realizes the "matter cloud" power distribution management system based on security transmission. The actual test results of the power distribution management system show that each component can run normally, complete the core functions of the power distribution management system, and remotely view and manage the power distribution device information. The distribution management system is feasible and practical, effectively reduces the labor cost, and has certain extensibility.

关键词： Distribution management system Data transmission security Remote loT cloud computing

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A Survey on Enhancing cloud Data Security Using Blockchain Technology 16

A Survey on Enhancing Cloud Data Security Using Blockchain T...

引用

16th IEEE international conference on Computational Intelligence and communication Networks, CICN 2024

作者： Narayanan, Neethi Celestin Vigila, S Maria Computer Science & Engineering Lbs Institute of Technology for Women Trivandrum India Information Technology Noorul Islam Center for Higher Education Kanyakumari India

ISBN: (纸本)9798331505264

cloud computing has transformed data storage and access, offering scalability and flexibility but also introducing significant security challenges. Blockchain technology offers potential answers to these problems because of its decentralized and unchangeable properties. This paper surveys existing research on implementing blockchain technology to improve cloud data security. By reviewing recent advancements and methodologies, this survey provides a comprehensive overview of current research trends, identifies gaps, and suggests future directions. Key areas of focus include access control, data integrity, and origin, highlighting how blockchain can mitigate common security threats in cloud environments. © 2024 IEEE.

关键词： cloud security

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A deep study of analysis for encryption and decryption algorithm in cloud data with machine learning techniques

A deep study of analysis for encryption and decryption algor...

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2024 international conference on communication, computing and Internet of Things, IC3IoT 2024

作者： Bharathi, M. Divya Latha, B. Sri Sai Ram Engineering College Department Of Computer Science And Engineering Tambaram Chennai India

ISBN: (纸本)9798350352689

An emergence of cloud computing has made secure search on encrypted cloud data a popular area of study. Previous techniques' limited ability to generate query trapdoors made them less effective at ensuring query secrecy. A data user can also readily examine the query results of another data user in these systems, as the data owner often has complete knowledge of the query results of the data users. In certain application settings, the data user could be reluctant to give away the privacy of their query to anybody but themselves. It provide a search technique that enhances privacy by letting the data user create a different random query trapdoor each time and also it suggest the security of our scheme and show through extensive experiments that it is exactly right. Put the suggested plan into practice and evaluate how well it performs in terms of key generation process, secure indexing, trapdoor creation, and search timing. Compared to current hashing and attribute-based encryption searchable encryption technologies, the suggested scheme outperforms them. So, contributed to plan into practice, assess, and contrast its results using the example of searchable algorithms for encryption © 2024 IEEE.

关键词： Cryptography

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Blockchain and Machine Learning for Optimized Resource Allocation in cloud computing Services 7

Blockchain and Machine Learning for Optimized Resource Alloc...

引用

7th international conference on Contemporary computing and Informatics, IC3I 2024

作者： Rangaiah, Yagateela Pandu Yaragudri, Hanamant Rani, K.Pushpa Singh, Navdeep Albawi, Ali Kalyani, Susmita Institute of Aeronautical Engineering Department of Electronics and Communication Enfineering Dundigal Hyderabad500043 India New Horizon College of Engineering Department of Mechanical Engineering Bangalore India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Lovely Professional University Phagwara India The Islamic University College of Medical Technology Radiology Techniques Department Najaf Iraq Lloyd Law College Plot No. 11 Knowledge Park II Uttar Pradesh Greater Noida201315 India

ISBN: (纸本)9798350350067

Resource efficiency becomes increasingly critical as cloud computing services alter. This article uses bitcoin and machine learning to optimize resource utilization. We study PRDA, BSCA, and DRAA algorithms and propose 'Blockchain and Machine Learning for Optimized Resource Allocation in cloud computing Services.' We employ blockchain, machine learning, and smart contracts to make resource sharing safer, clearer, and adaptable to cloud contexts. A comparative test demonstrates our resource allocation strategy works. PRDA reliably predicts resource usage using real-time data and prior patterns. This greatly reduces expenses and waste. The BSCA ensures safe and transparent delivery via guidelines. In multi-tenant cloud systems, DRAA optimizes resource consumption via reinforcement learning. This fixes underuse, exorbitant pricing, and speed loss. With this strategy, cloud service providers can remain open, keep rates low, and serve customers promptly. © 2024 IEEE.

关键词： Adversarial machine learning

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Advancing cloud Security Frameworks Implementing Distributed Ledger Technology for Robust Data Protection and Decentralized Security Management in cloud computing Environments 2

Advancing Cloud Security Frameworks Implementing Distributed...

引用

2nd IEEE international conference on Advances in Information Technology, ICAIT 2024

作者： Rajasekar, P. Kalaiselvi, K. Shanmugam, Raju Tamilselvan, S. Pandian, A. Pasumpon Department of ECE Sri Krishna College of Technology Kovaipudur Tamil Nadu Coimbatore India Department of Electronics and Communication Engineering Hindusthan College of Engineering and Technology Tamil Nadu Coimbatore India Unitedworld School of Computational Intelligence Karnavati University Gujarat India Department of Computer Science and Engineering Saveetha School of Engineering SIMATS Saveetha University Tamil Nadu Chennai India Department of Computer Science and Engineering CARE College of Engineering Tamilnadu Trichy India

ISBN: (纸本)9798350383867

cloud computing caused the paradigm shift in business performance, from scalability to flexibility as well as affordability in the management of computing resources. Nevertheless, ensuring security of the data remains a key issue in the cloud due to the centralized interactions between service provider and a single vulnerability in the network can put rest of the data at risk. Consequently, the application of DLT, in addition to other solutions such as DLT, demonstrates a big step towards the improvement of cloud security frameworks. This article focuses on the implementation of DLT for data protection applications that are based on a solid dataset and decentralized security procedures in cloud environments. DLT utilization, like blockchain, provides an organization with integrity data, transparency, and fitness to counter cyber threats. Architecture stacks up sponsors such as cloud providers, users, and applications and DLT is responsible for the security of the transaction and the security policy enforcement. Customers use those services via desktop based application with transparent security policy arisen from DLT. Moreover, DLT also does identity management in the way that is decentralized, data sharing in the manner that it is secure, and the compliance to regulatory frameworks, which in addition reduces the trust and privacy risks in the cloud ecosystems. The proposed architecture is genuinely a big jump toward protecting cloud security from centralized control interruptions and thus, enhancing resilience and stability in cloud computing. © 2024 IEEE.

关键词： cloud security

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QoS CBSC: An Enhanced Metaheuristic Strategy on QoS-cloud-based Service in cloud 5

QoS CBSC: An Enhanced Metaheuristic Strategy on QoS-Cloud-ba...

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5th international conference on Intelligent communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Jesy Janet Kumari, J. Thangam, S. Saleem Raja, A. Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India College of Computing and Information Sciences University of Technology and Applied Sciences-Shinas It Department Oman

ISBN: (纸本)9798350385649

Due to the growing number of cloud users working on various cloud apps on specific infrastructure, resource allocation in cloud computing is implicitly difficult. Most resource allocation strategies currently in use focused on delivering efficiency determined by the workload of applications across many domains, such as business and scientific. cloud service brokers compete strongly with one another to provide quality of service improvements based on the need, demand and the rapid growth of the services that are offered. Such conflict makes it difficult and complex to provide simple service selection and composition services in the cloud, this needs to be addressed to lighten the load on local resources. Because cloud-based services are too sophisticated and scalable, it is preferable to use an optimization strategy to choose the services that will meet the needs of the clients. To do this, a hybrid algorithm Modified Ant Colony System cloud Services Composition (MACSCSC) is proposed to employ Ant Colony Optimization (ACO) incorporated with Genetic Algorithm (GA) to smoothly increase cloud-based services. When allocating cloud resources these meta-heuristic algorithms can achieve significantly better performance, lower costs and instances, better utilization of resources, and increased energy efficiency. The empirical findings on different real datasets have been demonstrated to show the improvements of the suggested method to overcome the drawbacks such as allocation of resources and high power consumption. © 2024 IEEE.

关键词： Quality of service

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