بررسی استفاده از انواع روش‌های یادگیری عمیق در امنیت شبکه‌های اینترنت اشیا
محورهای موضوعی : مهندسی کامپیوتر
هادی مهدوی نیا
1
(دانشکده فنی مهندسي، واحد اصفهان (خوراسگان)، دانشگاه آزاد اسلامی، خوراسگان، اصفهان، ايران)
محمدرضا سلطان آقایی
2
(دانشکده فنی مهندسي، واحد اصفهان (خوراسگان)، دانشگاه آزاد اسلامی، خوراسگان، اصفهان، ايران)
مهدی اسماعیلی
3
(دانشکده برق و کامپیوتر، واحد کاشان، دانشگاه آزاد اسلامی، کاشان، اصفهان، ايران)
کلید واژه: روش‌های یادگیری عمیق, امنیت شبکه, اینترنت اشیا, امنیت اینترنت اشیا, رویکردهای یادگیری عمیق,
چکیده مقاله :
گسترش مداوم دستگاه‌های هوشمند در بسیاری از جنبه‌های زندگی روزمره ما همراه با تقاضای روزافزون برای مکانیسم‌های مناسب برای اطمینان از مقاومت آنها در برابر انواع مختلف تهدیدات و حملات در محیط اینترنت اشیا است. در این زمینه، یادگیری عمیق به عنوان یکی از موفق‌ترین و مناسب‌ترین تکنیک‌ها برای استفاده در جنبه‌های مختلف امنیت اینترنت اشیا در حال ظهور است. هدف این پژوهش، بررسی و تحلیل سیستماتیک چشم‌انداز تحقیقاتی در مورد رویکردهای یادگیری عمیق اعمال شده در سناریوهای مختلف امنیت اینترنت اشیا است. تحقیقات بررسی شده، بر اساس دیدگاه‌های مختلف در یک طبقه‌بندی منسجم و ساختاریافته به منظور شناسایی شکاف در این حوزه تحقیقاتی محوری طبقه‌بندی می‌شوند. این تحقیق بر روی مقالات مرتبط با کلمات کلیدی "یادگیری عمیق"، "امنیت" و "اینترنت اشیا" در چهار پایگاه داده اصلی IEEEXplore، ScienceDirect، SpringerLink و کتابخانه دیجیتال ACM متمرکز شده است. در پایان، 90 مقاله، انتخاب و بررسی شده است. این مطالعات با توجه به سه سؤال اصلی تحقیق، یعنی جنبه‌های امنیتی درگیر، معماری‌های شبکه یادگیری عمیق مورد استفاده و مجموعه داده‌های مورد استفاده در زمینه امنیت اینترنت اشیا انجام می‌شود. بحث نهایی، شکاف‌های تحقیقاتی را که باید بررسی شوند و اشکالات و آسیب‌پذیری‌های رویکردهای یادگیری عمیق در سناریوی امنیت اینترنت اشیا را برجسته می‌کند.
The development of smart devices in many aspects of our daily lives is accompanied by the increasing use of appropriate mechanisms to counter them against various attacks and applications in the Internet of Things environment. In this context, it is emerging as one of the most successful and suitable techniques for use in various aspects of IoT security. The aim of this is to systematically review and analyze research studies on research eyes conducted in different Internet of Things security scenarios. The reviewed researches are classified according to different perspectives in a coherent and structured classification to identify the gap in this research area. This research has been published on articles related to the keywords "concept learning", "security" and "Internet of Things" in the four main databases IEEEXplore, ScienceDirect, SpringerLink, and ACM Digital Library. In the end, 90 articles have been selected and reviewed. These studies are conducted according to three main research questions, i.e. the security aspects involved, the network architectures used, and the datasets used in IoT security. The final discussion explores the research gaps and acknowledges the outstanding flaws and vulnerabilities in the IoT security scenario.
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