Does Cloud Computing Matter? An Analysis of the Cloud Model Software-as-a-Service and Its Impact on Operational Agility

Fremdt, S.; Beck, Roman; Weber, Sven

doi:10.1109/hicss.2013.182

Cited by 17 publications

(14 citation statements)

References 24 publications

(41 reference statements)

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“…Privacy is a vital factor that prevents users from adopting IoT devices. Therefore, development should be accompanied with effective privacy protection for a successful IoT system deployment [94][95][96]. Moreover, multi-tenancy, which is one of the main features of cloud computing, can cause security threats that may lead to private information leakage.…”

Section: ) Cloud Service Surfacementioning

confidence: 99%

A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security

Al-Garadi

Mohamed

Al-Ali

et al. 2020

IEEE Commun. Surv. Tutorials

776

333

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The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. It is one of the fastest developing fields in the history of computing, with an estimated 50 billion devices by the end of 2020. On the one hand, IoT technologies play a crucial role in enhancing several real-life smart applications that can improve life quality. On the other hand, the crosscutting nature of IoT systems and the multidisciplinary components involved in the deployment of such systems have introduced new security challenges. Implementing security measures, such as encryption, authentication, access control, network security and application security, for IoT devices and their inherent vulnerabilities is ineffective. Therefore, existing security methods should be enhanced to secure the IoT ecosystem effectively. Machine learning and deep learning (ML/DL) have advanced considerably over the last few years, and machine intelligence has transitioned from laboratory curiosity to practical machinery in several important applications. The ability to monitor IoT devices intelligently provides a significant solution to new or zero-day attacks. ML/DL are powerful methods of data exploration for learning about 'normal' and 'abnormal' behaviour according to how IoT components and devices perform within the IoT environment. Consequently, ML/DL methods are important in transforming the security of IoT systems from merely facilitating secure communication between devices to security-based intelligence systems. The goal of this work is to provide a comprehensive survey of ML methods and recent advances in DL methods that can be used to develop enhanced security methods for IoT systems.IoT security threats that are related to inherent or newly introduced threats are presented, and various potential IoT system attack surfaces and the possible threats related to each surface are discussed. We then thoroughly review ML/DL methods for IoT security and present the opportunities, advantages and shortcomings of each method. We discuss the opportunities and challenges involved in applying ML/DL to IoT security. These opportunities and challenges can serve as potential future research directions.

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Section: ) Cloud Service Surfacementioning

confidence: 99%

A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security

Al-Garadi

Mohamed

Al-Ali

et al. 2020

IEEE Commun. Surv. Tutorials

776

333

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“…Bu nedenle işletmelerin çevik bir yapıya sahip olmaları, başarı elde edebilmeleri ve hatta hayatta kalmaları için oldukça önemlidir (Huang, Ouyang, Pan, & Chou, 2012, s. 294). Çeviklik, bir işletmenin değişen ortamlara uyum sağlama yeteneğini ifade etmektedir (Fremdt, Beck, & Weber, 2013, s. 1026. Literatürde çeviklik; müşteri, iş ortaklığı ve operasyonel çeviklik olmak üzere genelde üç boyutta ele alınmaktadır (Akhtar, Khan, Tarba, & Jayawickrama, 2018, s. 308;Fremdt, Beck, & Weber, 2013, s. 1026.…”

Section: Operasyonel çEviklikunclassified

“…Çeviklik, bir işletmenin değişen ortamlara uyum sağlama yeteneğini ifade etmektedir (Fremdt, Beck, & Weber, 2013, s. 1026. Literatürde çeviklik; müşteri, iş ortaklığı ve operasyonel çeviklik olmak üzere genelde üç boyutta ele alınmaktadır (Akhtar, Khan, Tarba, & Jayawickrama, 2018, s. 308;Fremdt, Beck, & Weber, 2013, s. 1026. Müşteri çevikliği, bir işletmenin pazar fırsatlarını araştırırken ve değerlendirirken müşterileriyle iş birliği yapmasını ifade etmektedir.…”

Section: Operasyonel çEviklikunclassified

“…Kitlesel kişiselleştirme için gerekli olan bir diğer kavram ise çevikliktir. Çeviklik; operasyonel çeviklik, iş ortaklığı çevikliği ve müşteri çevikliği olmak üzere genelde üç boyutta ele alınmaktadır (Akhtar, Khan, Tarba, & Jayawickrama, 2018, s. 308;Fremdt, Beck, & Weber, 2013, s. 1026. Bu çalışmada sadece operasyonel çeviklik üzerinde durulacaktır.…”

Section: Introductionunclassified

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Tedari̇k Zi̇nci̇ri̇ Entegrasyonu, Operasyonel Çevi̇kli̇k Ve Ki̇tlesel Ki̇şi̇selleşti̇rme Yeteneği̇: İmalat Sektöründe Ampi̇ri̇k Bi̇r Araştirma

Çankaya

Can

2021

Sosyal Ekonomik Araştırmalar Dergisi

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Amaç -Bu çalışmada tedarik zinciri entegrasyonunun, operasyonel çeviklik ve kitlesel kişiselleştirme yeteneği üzerindeki etkisinin incelenmesi amaçlanmaktadır. Yöntem -Araştırmada Türkiye'de faaliyet gösteren imalat işletmeleri arasından kolayda örnekleme metodu ile seçilmiş 83 işletme üzerinde anket çalışması gerçekleştirilmiştir. Araştırma amacına ulaşmak ve bu doğrultuda geliştirilen hipotezleri test etmek için kısmi en küçük kareler yapısal eşitlik modeli (PLS-YEM) tercih edilmiştir. Bulgular -83 işletme üzerinde yapılan analizlerle tedarik zinciri entegrasyonunun üç boyutundan sadece iç entegrasyonun operasyonel çeviklik ile pozitif ilişkili olduğu ayrıca müşteri ve tedarikçi entegrasyonunun kitlesel kişiselleştirme yeteneği ile pozitif ilişkili olduğu tespit edilmiştir. Sonuç -Araştırma sonuçlarına göre, tedarik zinciri entegrasyonunun bazı boyutlarının operasyonel çevikliğin ve kitlesel kişiselleştirme yeteneğinin gelişmesini olumlu bir şekilde etkileyeceği söylenebilir.

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“…Consequently, agility is crucial for firms, especially in volatile environments, to stay competitive. In this regard, IT plays an important role in sensing and responding capabilities [ 38 ]. Peng et al [ 39 ] proposed a framework for resource provisioning in the cloud through network vitalization.…”

Section: Service Provisioning Requirementsmentioning

confidence: 99%

A Study on Strategic Provisioning of Cloud Computing Services

Whaiduzzaman

Haque

Chowdhury

et al. 2014

The Scientific World Journal

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Cloud computing is currently emerging as an ever-changing, growing paradigm that models “everything-as-a-service.” Virtualised physical resources, infrastructure, and applications are supplied by service provisioning in the cloud. The evolution in the adoption of cloud computing is driven by clear and distinct promising features for both cloud users and cloud providers. However, the increasing number of cloud providers and the variety of service offerings have made it difficult for the customers to choose the best services. By employing successful service provisioning, the essential services required by customers, such as agility and availability, pricing, security and trust, and user metrics can be guaranteed by service provisioning. Hence, continuous service provisioning that satisfies the user requirements is a mandatory feature for the cloud user and vitally important in cloud computing service offerings. Therefore, we aim to review the state-of-the-art service provisioning objectives, essential services, topologies, user requirements, necessary metrics, and pricing mechanisms. We synthesize and summarize different provision techniques, approaches, and models through a comprehensive literature review. A thematic taxonomy of cloud service provisioning is presented after the systematic review. Finally, future research directions and open research issues are identified.

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Does Cloud Computing Matter? An Analysis of the Cloud Model Software-as-a-Service and Its Impact on Operational Agility

Cited by 17 publications

References 24 publications

A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security

A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security

Tedari̇k Zi̇nci̇ri̇ Entegrasyonu, Operasyonel Çevi̇kli̇k Ve Ki̇tlesel Ki̇şi̇selleşti̇rme Yeteneği̇: İmalat Sektöründe Ampi̇ri̇k Bi̇r Araştirma

A Study on Strategic Provisioning of Cloud Computing Services

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