دوره 22، شماره 2 - ( 6-1404 )
جلد 22 شماره 2 صفحات 64-43 |
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sarhadi Z, khazaiepoor M. A detection system for smart cities Using a neural network and Sailfish Optimizer algorithm. JSDP 2025; 22 (2) : 3
URL: http://jsdp.rcisp.ac.ir/article-1-1378-fa.html
URL: http://jsdp.rcisp.ac.ir/article-1-1378-fa.html
سرحدی زهرا، خزاعی پور مهدی. یک سامانه تشخیص نفوذ برای شهرهای هوشمندبا استفاده از شبکه عصبی و الگوریتم اره‌ماهی. پردازش علائم و داده‌ها. 1404; 22 (2) :43-64
دانشجوی دکترا، گروه مهندسی کامپیوتر، دانشکده فنی‌ومهندسی، واحد بیرجند، دانشگاه آزاد اسلامی، بیرجند، ایران
چکیده: (275 مشاهده)
اینترنت اشیا (IoT) شبکه‌ای گسترده از اشیای هوشمند متصل به اینترنت است که در شهرهای هوشمند برای یک‌پارچه‌سازی سامانه‌هایی مانند حمل‌ونقل، برق و بهداشت کاربرد دارد. یکی از چالش‌های مهم در شبکه‌های IoT حملات سایبری است که موجب اختلال در سرویس‌ها می‌شود. برای مقابله با این تهدیدات استفاده از سامانه‌های تشخیص نفوذ مبتنی بر یادگیری ماشین ضروری است. در این مقاله روشی ترکیبی برای تشخیص حملات به شهرهای هوشمند ارائه شده‌است که شامل سه مرحله است: ۱) متعادل‌سازی داده‌ها با تئوری بازی و شبکه GAN، ۲) انتخاب ویژگی با الگوریتم بهینه‌سازی اره‌ماهی، ۳) تنظیم پارامترهای ماشین بردار پشتیبان (SVM) با الگوریتم‌های محاسبات ریاضی. شبکه عصبی چندلایه برای تحلیل ویژگی‌ها و SVM برای طبقه‌بندی ترافیک استفاده شده‌اند. نتایج آزمایش‌ها روی مجموعه‌داده NSL-KDD در نرم‌افزار MATLAB، دقت 99.12 درصد، حساسیت 98.92 درصد و صحت 98.96 درصد را نشان می‌دهد. روش پیشنهادی نسبت به الگوریتم‌های گرگ خاکستری و ژنتیک عملکرد دقیق‌تری دارد.
شماره‌ی مقاله: 3
واژه‌های کلیدی: اینترنت اشیا، شهرهای هوشمند، سامانه تشخیص نفوذ، یادگیری ماشین، الگوریتم اره‌ماهی، انتخاب ویژگی
نوع مطالعه: پژوهشي |
موضوع مقاله:
مقالات پردازش تصویر
دریافت: 1402/2/7 | پذیرش: 1404/4/30 | انتشار: 1404/6/22 | انتشار الکترونیک: 1404/6/22
دریافت: 1402/2/7 | پذیرش: 1404/4/30 | انتشار: 1404/6/22 | انتشار الکترونیک: 1404/6/22
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