Journal ArticleDOI
SMS Spam Detection Using Noncontent Features
TLDR
This service-side solution uses graph data mining to distinguish spammers from nonspammers and detect spam without checking a message's contents.Abstract:
Short Message Service text messages are indispensable, but they face a serious problem from spamming. This service-side solution uses graph data mining to distinguish spammers from nonspammers and detect spam without checking a message's contents.read more
Citations
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Proceedings ArticleDOI
A survey on behaviors exhibited by spammers in popular social media networks
TL;DR: The authors survey the related literature that identifies the presence of spam as well as spammers in popular social media networks and Twitter is a target platform for promoters and spammers.
Book ChapterDOI
A Review of Feature Extraction Optimization in SMS Spam Messages Classification
TL;DR: The focus of this study is to excavate the features extraction in classifying SMS spam messages at users’ end and offer a motivational effort for further execution in a wider perspective of combating spam such as measurement of spam’s risk level.
Proceedings ArticleDOI
Understanding SMS spam in a large cellular network
TL;DR: This study conducts a comprehensive study of SMS spam in a large cellular network in the US and finds that spam numbers within the same activity often exhibit strong similarity in terms of their sending patterns, tenure and geolocations.
Journal ArticleDOI
An Adaptive and Collaborative Server-Side SMS Spam Filtering Scheme Using Artificial Immune System
TL;DR: A comprehensive experimental analysis on the SMS data set reveals the constant changes of Spam keywords and the impact of user feedback for system adaptability, and showed that ExAIS_SMS is an efficient SMS Spam filtering technique, especially in resource constrained mobile phones.
An Approach for SMS Spam Detection
TL;DR: The DND service restrict only the SMS send through SMS gateways and detects these mess ages sent through spammers mobile and restrict it.
References
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EigenRank: a ranking-oriented approach to collaborative filtering
Nathan Liu,Qiang Yang +1 more
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