مقاله انگلیسی رایگان در مورد پذیرش امنیت سایبری یادگیری ماشینی در شرکت های کوچک و متوسط – MDPI 2021

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مشخصات مقاله
ترجمه عنوان مقاله پذیرش امنیت سایبری یادگیری ماشینی در شرکت های کوچک و متوسط در کشورهای توسعه یافته
عنوان انگلیسی مقاله Machine Learning Cybersecurity Adoption in Small and Medium Enterprises in Developed Countries
انتشار مقاله سال ۲۰۲۱
تعداد صفحات مقاله انگلیسی  ۲۷ صفحه
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پایگاه داده  نشریه MDPI
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نمایه (index) Master Journal List – Scopus – DOAJ
نوع مقاله
ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
۲٫۶۰۴ در سال ۲۰۲۰
شاخص H_index ۱۹ در سال ۲۰۲۱
شاخص SJR ۰٫۴۰۴ در سال ۲۰۲۰
شناسه ISSN ۲۰۷۳-۴۳۱X
شاخص Quartile (چارک) Q2 در سال ۲۰۲۰
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رشته های مرتبط مدیریت، مهندسی کامپیوتر، فناوری اطلاعات
گرایش های مرتبط اینترنت و شبکه های گسترده، امنیت اطلاعات، مدیریت کسب و کار
نوع ارائه مقاله
ژورنال
مجله / کنفرانس کامپیوترها – Computers
دانشگاه Cardiff School of Technologies, Cardiff Metropolitan University, Wales, UK
شناسه دیجیتال – doi https://doi.org/10.3390/computers10110150
کد محصول E15850
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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Abstract

In many developed countries, the usage of artificial intelligence (AI) and machine learning (ML) has become important in paving the future path in how data is managed and secured in the small and medium enterprises (SMEs) sector. SMEs in these developed countries have created their own cyber regimes around AI and ML. This knowledge is tested daily in how these countries’ SMEs run their businesses and identify threats and attacks, based on the support structure of the individual country. Based on recent changes to the UK General Data Protection Regulation (GDPR), Brexit, and ISO standards requirements, machine learning cybersecurity (MLCS) adoption in the UK SME market has become prevalent and a good example to lean on, amongst other developed nations. Whilst MLCS has been successfully applied in many applications, including network intrusion detection systems (NIDs) worldwide, there is still a gap in the rate of adoption of MLCS techniques for UK SMEs. Other developed countries such as Spain and Australia also fall into this category, and similarities and differences to MLCS adoptions are discussed. Applications of how MLCS is applied within these SME industries are also explored. The paper investigates, using quantitative and qualitative methods, the challenges to adopting MLCS in the SME ecosystem, and how operations are managed to promote business growth. Much like security guards and policing in the real world, the virtual world is now calling on MLCS techniques to be embedded like secret service covert operations to protect data being distributed by the millions into cyberspace. This paper will use existing global research from multiple disciplines to identify gaps and opportunities for UK SME small business cyber security. This paper will also highlight barriers and reasons for low adoption rates of MLCS in SMEs and compare success stories of larger companies implementing MLCS. The methodology uses structured quantitative and qualitative survey questionnaires, distributed across an extensive participation pool directed to the SMEs’ management and technical and non-technical professionals using stratify methods.

۱٫ Introduction

SMEs face a fight for balance when it comes to keeping their data safe and secure. With cyber-attacks rising due to the increase of smart technologies, standard measures are being put in place in line with recent changes to the law, Brexit, UK GDPR, and Cyber Essentials [1] amongst many others. SMEs struggle to understand the bigger concepts of how AI and ML could help. Getting these standards in place requires an intervention to current safety measures of cyber security, and control of varied connections and interactions on the internet.

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