Mitigating spam using network-level features
نویسنده
چکیده
منابع مشابه
An Effective Model for SMS Spam Detection Using Content-based Features and Averaged Neural Network
In recent years, there has been considerable interest among people to use short message service (SMS) as one of the essential and straightforward communications services on mobile devices. The increased popularity of this service also increased the number of mobile devices attacks such as SMS spam messages. SMS spam messages constitute a real problem to mobile subscribers; this worries telecomm...
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Filtering image email spam is considered to be a challenging problem because spammers keep modifying the images being used in their campaigns by employing different obfuscation techniques. Therefore, preventing text recognition using Optical Character Recognition (OCR) tools and imposing additional challenges in filtering such type of spam. In this paper, we propose an image spam filtering tech...
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Deceptive opinion spam detection has attracted significant attention from both business and research communities. Existing approaches are based on manual discrete features, which can capture linguistic and psychological cues. However, such features fail to encode the semantic meaning of a document from the discourse perspective, which limits the performance. In this paper, we empirically explor...
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Rapidly growing micro-blogging social networks, such as Twitter, have been infiltrated by large number of spam accounts. Limited to 140 characters, Twitter spam is often vastly different from traditional email spam and link spam such that conventional methods of content-based spam filtering are insufficient. Many researchers have proposed schemes to detect spammers on Twitter. Most of these sch...
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تاریخ انتشار 2011