روشی بهینه برای تشخیص ناهنجاری ها در سیستم های تشخیص نفوذ
الموضوعات :
1 - عضو هییت علمی گروه مهندسی کامپیوتر/دانشگاه پیام نور
الکلمات المفتاحية: یادگیری ماشین, امنیت , سیتم تشخیص نفوذ, شبکه های نرم افزار محور,
ملخص المقالة :
شبکه های نرم افزارمحور به عنوان معماری ازشبکه های کامپیوتری نوین با استفاده از کنترل کننده مرکزی در نظر گرفته می شوند. هر گونه تغییر در داده های شبکه و ترتیب آن می تواند به صورت بی دردسر در نرم افزار از طریق کنترل کننده در این شبکه ها اجرا شود. در نتیجه، شناسایی و پاسخ به موقع به حملات سایبری مانند حمله منع سرویس توزیع شده (DDoS)می تواند به دست آید که در شبکه های معمولی چنین نیست. در این روش، از تریشولد آلفا وروشهای یادگیری ماشین برای تشخیص ناهنجاری ها استفاده می شود. نتایج با اعتبارسنجی متقابل ۱۰ برابری ارزیابی می شوند. مجموعه داده مورد استفاده ISOT، CTU-13و UNB ISCX است. نتایج ارزیابی با دقت ۹۹.۸۴% و مقدار FPR ، 0.1% نشان دهنده کارایی بالای مدل پیشنهادی در شبکه های SDN است.
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