اینترنت اشیا (IoT) و رایانش لبه ای
ترجمه نشده

اینترنت اشیا (IoT) و رایانش لبه ای

عنوان فارسی مقاله: مدل CAAVI-RICS برای رعایت امنیت سیستم های توزیع شده اینترنت اشیا (IoT) و رایانش لبه ای
عنوان انگلیسی مقاله: CAAVI-RICS Model for Observing the Security of Distributed IoT and Edge Computing Systems
مجله/کنفرانس: عمل و نظریه مدل سازی شبیه سازی – Simulation Modelling Practice and Theory
رشته های تحصیلی مرتبط: مهندسی کامپیوتر، مهندسی فناوری اطلاعات
گرایش های تحصیلی مرتبط: امنیت اطلاعات، رایانش ابری، اینترنت و شبکه های گسترده
کلمات کلیدی فارسی: رایانش لبه ای، اینترنت اشیا (IoT)، امنیت سایبری، امنیت توزیع شده
کلمات کلیدی انگلیسی: Edge computing, IoT, cyber-security, distributed security
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.simpat.2020.102125
دانشگاه: University of Novi Sad, Faculty of Sciences, Trg Dositeja Obradovi´ca 4, Novi Sad, Serbia
صفحات مقاله انگلیسی: 31
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2020
ایمپکت فاکتور: 3.271 در سال 2019
شاخص H_index: 58 در سال 2020
شاخص SJR: 0.726 رد سال 2019
شناسه ISSN: 1569-190X
شاخص Quartile (چارک): Q1 در سال 2019
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E14995
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

۱٫ Introduction

۲٫ Related Work

۳٫ Methodological Security Overview Framework for ECP Architectures – CAAVI

۴٫ Bridging CAAVI Principles

۵٫ Conclusion

References

بخشی از مقاله (انگلیسی)

Abstract

The pervasive integration of ‘things‘ in the Internet of Things together with state-of-the-art computer systems provide a stimulating environment for creativity and business opportunities, but also a large range of security challenges. Engineering the security of such systems must acknowledge the peculiar conditions under which such systems operate: low computational capacity, distributed decision-making, significant node churn, etc. These conditions must, therefore, be supported by the techniques and methodologies for building secure and robust IoT systems. With CAAVI-RICS methodology we explore credibility, authentication, authorization, verification, and integrity of IoT and edge computing systems, through explaining the rationale, influence, concerns, and security solutions that accompany them. Our contribution is a complete and detailed systematic categorization and streamlining of security problems, covering the security environment of IoT and edge computing systems. Besides, we contribute to the debate on key aspects of edge computing security and state-of-the-art solutions.

Introduction

Since its appearance, cloud computing has provided the easiest way to remotely store and access data and services. Cloud computing has rapidly brought about a revolution in how we develop our services and applications by providing on-demand self-service, multi-tenant processing resources, broad network access, pooling of resources, fast provisioning, and rapid elasticity. Despite its capacity, the cloud-based application building model does not extend to use-cases where disrupting time-sensitive functionalities and inducing higher latency can result in catastrophic events (e.g. vehicle-to-vehicle communication). Even though the cloud offers a range of advantages, it introduces new concerns about security, privacy, availability of data and services, reliability, and performance. Hence the concepts of the Internet of Things (IoT) and Edge Computing (ECP) systems. IoT cyber-physical systems are enabled through a multitude of technological innovations: on-demand adaptive resource management frameworks, lightweight communication, and data protection protocols, etc. ECP is a computational framework/deployment methodology where data analytics and decision-making processes are moved from cloud closer to data sources, i.e. to the edge of the network. ECP vastly reduces the volume of data that is sent through the network, improves overall system security, responsiveness, and latency.