کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
392370 | 664765 | 2014 | 15 صفحه PDF | دانلود رایگان |

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.
Journal: Information Sciences - Volume 289, 24 December 2014, Pages 133–147