کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
392370 664765 2014 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Feature set identification for detecting suspicious URLs using Bayesian classification in social networks
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Feature set identification for detecting suspicious URLs using Bayesian classification in social networks
چکیده انگلیسی

Social network services (SNSs) are increasing popular. Communicating with friends forms a social network that can be used to promptly share information with friends. In targeted attacks, SNSs are often used to collect personal information and craft attacks based on a specific user profile. Malware can be used to facilitate social relationship, sends messages containing malicious URLs, lures users to click on these URLs by employing social engineering techniques; then replicates through the social network over and over again. Because users are curious and trust in their friends, they typically click on malicious URLs without verification. In this study, a feature set is presented that combines the features of traditional heuristics and social networking. Furthermore, a suspicious URL identification system for use in social network environments is proposed based on Bayesian classification. The experimental results indicate that the proposed approach achieves a high detection rate.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 289, 24 December 2014, Pages 133–147
نویسندگان
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