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شناسایی وب سایت فیشینگ در بانکداری اینترنتی با استفاده از الگوریتم بهینه سازی صفحات شیب‌دار | ||
| پدافند الکترونیکی و سایبری | ||
| مقاله 3، دوره 3، شماره 1، اردیبهشت 1394، صفحه 29-39 اصل مقاله (790.58 K) | ||
| نویسندگان | ||
| نفیسه لنگری* 1؛ مجید عبدالرزاق نژاد2 | ||
| 1کارشناسی ارشد، دانشکده فنی و مهندسی، دانشگاه بیرجند، بیرجند، ایران | ||
| 2استادیار، دانشکده فنی و مهندسی، دانشگاه بزرگمهر قائنات، قائنات، ایران | ||
| تاریخ دریافت: 30 مهر 1393، تاریخ بازنگری: 31 خرداد 1402، تاریخ پذیرش: 28 شهریور 1397 | ||
| چکیده | ||
| یکی از عوامل بسیار تأثیر گذار در توسعه تجارت الکترونیک و تجارت تحت وب، امنیت آن می‌باشد. اما متناسب با توسعه تجارت الکترونیک، مقوله فیشینگ و سرقت اطلاعات بانکی افراد به تهدید بسیار جدی در این حوزه بدل شده است. روش‌های متنوعی در شناسایی وب سایت فیشینگ مورد بررسی و تحلیل قرار گرفته‌اند. در اکثر روش‌ها توجهی به طول عمر کوتاه وب سایت فیشینگ و تلاش برای کاهش حجم محاسباتی صورت نگرفته است. از این جهت، در این پژوهش سعی شده تا ویژگی‌های پراهمیت را جهت ارزیابی وب سایت فیشینگ استخراج کرده و سپس با استفاده از الگوریتم بهینه سازی صفحات شیب‌دار فرآیند طبقه بندی انجام گیرد. مقایسه نتایج حاصله از این رویکرد جدید با بهترین روش‌های موجود، اثبات کننده توانایی این رویکرد در شناسایی وب سایت-های فیشینگ می‌باشد. | ||
| کلیدواژه‌ها | ||
| تشخیص وب سایت فیشینگ؛ بانکداری اینترنتی؛ الگوریتم بهینه سازی صفحات شیب‌دار؛ استخراج ویژگی؛ طبقه‌بندی | ||
| عنوان مقاله [English] | ||
| Phishing Website Detection for e-Banking by Inclined Planes Optimization Algorithm | ||
| نویسندگان [English] | ||
| Nafiseh Langhari1؛ Majid Abdolrazzagh Nejad2 | ||
| 1Master's degree, Technical and Engineering Faculty, Birjand University, Birjand, Iran | ||
| 2Assistant Professor, Technical and Engineering Faculty, Bozormehr Qaenat University, Qaenat, Iran | ||
| چکیده [English] | ||
| One of the most important factors influencing the development of e-commerce and web-based commerce is security. However development of e-commerce leads to phishing and steal the customer information. So the various methods have been designed to detect phishing websites in the literature. Lacks of attention to the short lifetime of phishing website, and to reduce the amount of computation are the main gaps of these methods. In this paper, a new intelligent approach is proposed to detect phishing websites, in e-banking by extracting sensitive features of websites on phishing attacks and classifying candidate websites in three classes such as phishing, legitimate and suspicious websites based on inclined planes optimization algorithm. The comparison results of the new intelligent approach with the best available techniques, demonstrate the ability of this approach to detect phishing websites. | ||
| کلیدواژه‌ها [English] | ||
| Network Security, Service Security, Port Security, Authentication, Port-Knocking | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 707 تعداد دریافت فایل اصل مقاله: 475 |
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