The Impact of Machine Learning on Cybersecurity in Social Networks

  • سال انتشار: 1404
  • محل انتشار: بیست و ششمین کنفرانس بین المللی فناوری اطلاعات، کامپیوتر و مخابرات
  • کد COI اختصاصی: ITCT26_013
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 84
دانلود فایل این مقاله

نویسندگان

Hossein Omidi Zadeh

Faculty of Informatics, University of Debrecen, Kassai út ۲۶, ۴۰۲۸ Debrecen, Hungary

چکیده

In recent years, the proliferation of social networks has significantly increased the volume and sensitivity of user-generated content, making these platforms attractive targets for cyber threats. Traditional cybersecurity mechanisms have proven inadequate in detecting sophisticated and evolving attacks such as phishing, malware distribution, and identity theft. Machine Learning (ML) has emerged as a powerful tool in enhancing cybersecurity by enabling systems to learn from historical data, identify patterns, and predict malicious activities in real-time. This study investigates the impact of ML techniques—including Supervised Learning (SL), Unsupervised Learning (UL), and Reinforcement Learning (RL)—on improving cybersecurity in social networks. We explore how ML algorithms such as Support Vector Machines (SVM), Random Forest (RF), and Deep Neural Networks (DNN) can be applied to detect anomalies, spam, and coordinated attacks with high accuracy. The integration of ML into Intrusion Detection Systems (IDS) and User Behavior Analytics (UBA) is also examined. The findings indicate that ML not only enhances threat detection capabilities but also reduces false positives and response time. This research highlights the critical role of ML in the development of intelligent, adaptive, and proactive security frameworks for social networking platforms.

کلیدواژه ها

Machine Learning, User Behavior Analytics, Deep Neural Networks, Intrusion Detection Systems, Social Networks, Reinforcement Learning

مقالات مرتبط جدید

اطلاعات بیشتر در مورد COI

COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.

کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.