A comparative Analysis on Stacked Hybrid Intelligence: A Multi-Paradigm Machine Learning Framework for Robust Phishing URL Detection
DOI:
https://doi.org/10.65405/gcfgsj10الكلمات المفتاحية:
Phishing URL detection; Hybrid ensemble learning; PhiUSIIL dataset; Character-level CNN; Bi-LSTM; Stacked generalization; Cybersecurityالملخص
يتطلب التطور المتزايد لحملات التصيد الاحتيالي أطر عمل للكشف تتجاوز المصنفات التقليدية أحادية النموذج. تقدم هذه الدراسة تقييمًا شاملًا لستة بنى تعلّم آلي متميزة، تشمل أساليب التجميع التقليدية، والمصنفات القائمة على النواة، وبنى الشبكات العصبية العميقة، وذلك بتطبيقها على مجموعة بيانات PhiUSIIL التي تضم 235,795 عنوان URL غنية بالميزات المعجمية والمتعلقة بالمضيف. يطبق هذا البحث خوارزميات الغابة العشوائية (RF)، وXGBoost، والشبكات العصبية الالتفافية على مستوى الأحرف (CNN)، وشبكات الذاكرة طويلة المدى ثنائية الاتجاه (Bi-LSTM)، وآلات المتجهات الداعمة (SVM) ذات نواة دالة الأساس الشعاعي، بالإضافة إلى نموذج تجميع هجين مكدس جديد يدمج خوارزميات RF وXGBoost وSVM من خلال التعلم الفائق. أظهرت عملية التحقق المتقاطع الصارمة ذات الخمس طيات أن هذا النموذج الهجين البحثي يحقق أداءً فائقًا بدقة 98.73%، ودرجة F1 بنسبة 98.91%، ومساحة تحت منحنى ROC بنسبة 99.04%، متفوقًا على النماذج الفردية بنسبة 1.8-3.4% في المقاييس الحاسمة، مع الحفاظ على متانته في مواجهة عدم توازن الفئات (نسبة المواقع الشرعية إلى مواقع التصيد الاحتيالي 1.34:1). وكشف تحليل الميزات أن ميزات عناوين URL الهيكلية، مثل معدل استمرار الأحرف واحتمالية وجود حرف في عنوان URL، تُسهم بشكل غير متناسب في فعالية الكشف مقارنةً بمؤشرات سمعة المضيف. كما أثبت التحليل الحسابي أن أساليب تعزيز التدرج توفر أفضل توازن بين الدقة وزمن الاستجابة للنشر الفوري، في حين تتفوق البنى العميقة في التقاط الأنماط التسلسلية المعقدة، ولكنها تتكبد زمن استجابة استدلال أعلى بمقدار 4.7 مرة. يوفر هذا العمل للممارسين إرشادات مُثبتة تجريبيًا لاختيار النموذج في ظل قيود تشغيلية متنوعة، ويضع معيارًا جديدًا للذكاء الهجين في الكشف عن التهديدات السيبرانية. الكلمات المفتاحية: كشف روابط التصيد الاحتيالي؛ التعلم التجميعي الهجين؛ مجموعة بيانات PhiUSIIL؛ شبكة عصبية تلافيفية على مستوى الأحرف؛ شبكة عصبية ثنائية المدى طويلة المدى؛ التعميم المكدس؛ الأمن السيبراني.
التنزيلات
المراجع
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