MALT: Parallel Prediction of Malicious Tweets.

IEEE Transactions on Computational Social Systems(2018)

引用 14|浏览10
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摘要
It has been reported that embedded URLs and multimodal content (images, video, and sound recordings) in tweets are increasingly used to seduce users into a “wrong click,” leading to malware infection. In this paper, we predict whether a tweet is malicious or not by examining five classes of features: textual content including sentiment, paths emanating from a URL mentioned in the tweet, attributes...
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关键词
Security,Twitter,Feature extraction,Malware,Phishing,Machine learning,Predictive models,Uniform resource locators
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