تشخیص کاربران جعلی در شبکه‌های اجتماعی با استفاده از تحلیل مولفه‌های اصلی و الگوریتم تخمین چگالی هسته(مطالعه موردی: روی شبکه اجتماعی توئیتر)

نوع مقاله : مقاله پژوهشی

نویسنده

مربی، گروه کامپیوتر، دانشگاه آزاد اسلامی واحد رامهرمز، رامهرمز، ایران

چکیده

استفاده از شبکه‌های اجتماعی به شکل فزاینده‌ای در حال رشد است و افراد زمان زیادی از وقت خود را صرف استقاده از این شبکه‌ها می‌کنند. افراد مشهور و شرکت‌ها از این شبکه‌ها برای ارتباط با طرفداران و مشتریان خود استفاده کرده و آژانس‌های خبری برای توزیع خبر از این شبکه‌ها استفادهمی‌کنند. در راستای ترقی محبوبیت و رواج شبکه‌های اجتماعی بر خط، خطرات و تهدیدات امنیتی نیز درحال افزایش است و انجام فعالیت‌های مخرب و حملاتی از قبیل فیشینگ، ایجاد کاربرانجعلی و اسپم‌ها در این شبکه‌هاافزایش چشمگیری داشته است. در حمله ایجاد کاربر جعلی، کاربران مخرب با ایجاد کاربر جعلی خود را به جای افراد معرفی می‌کنند و از این طریق از شهرت افراد یا شرکت‌ها سوء استفاده می‌کنند.در این مقاله یک روش جدید برای کشف کاربران جعلی در شبکه‌های اجتماعی بر پایه الگوریتم‌های یادگیری ماشین ارائه می‌شود. در روش پیشنهادی برای آموزش ماشین از ویژگی‌های شباهت مختلفی مانند شباهت کسینوس، شباهت جاکارد، شباهت شبکه دوستی و معیارهای مرکزیت استفاده می‌شود که همهاین ویژگی‌ها از ماتریس مجاورت گراف شبکه اجتماعی استخراج می‌شوند. در ادامه جهت کاهش ابعاد داده‌ها و حل مشکل بیش برازش از تحلیل مولفه‌های اصلی استفاده شد. سپس با استفاده از دسته‌بندهایتخمین چگالی هسته و الگوریتم شبکه عصبی خود سازمان‌ده داده‌ها دسته‌بندی شده و نتایج روش پیشنهادی با استفاده از معیارهای دقت، حساسیت ونرخ تشخیص اشتباه ارزیابی می‌شود. بررسی نتایج نشان می‌دهد، روش پیشنهادی با دقت6/99% کاربرانجعلی را تشخیص می‌دهد که نسبت به روش کاوو حدود 5% بهبود یافته است، همچنین نرخ تشخیص اشتباه کاربرانجعلی نیز نسبت به همین روش 3% بهبود پیدا کرد.

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