Research on Spam SMS Detection and Prevention on Android Platform
نویسندگان
چکیده
منابع مشابه
SMS Spam Detection using Machine Learning Approach
Over recent years, as the popularity of mobile phone devices has increased, Short Message Service (SMS) has grown into a multi-billion dollars industry. At the same time, reduction in the cost of messaging services has resulted in growth in unsolicited commercial advertisements (spams) being sent to mobile phones. In parts of Asia, up to 30% of text messages were spam in 2012. Lack of real data...
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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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In this article, we develop a real-time mobile phone-based gaze tracking and eye-blink detection system on Android platform. Our eye-blink detection scheme is developed based on the time difference between two open eye states. We develop our system by finding the greatest circle—pupil of an eye. So we combine the both Haar classifier and Normalized Summation of Square of Difference template-mat...
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Smartphones contain security-sensitive information of a user such as contacts, SMS, photos, and GPS information. Because smartphones are always turned on and ready to connect to the Internet, that sensitive information is in danger of leakage. Various kinds of malware are more and more attacking smartphones, especially Android phones. We propose a scheme that protects Android phones against one...
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The Short Message Service (SMS) have an important economic impact for end users and service providers. Spam is a serious universal problem that causes problems for almost all users. Several studies have been presented, including implementations of spam filters that prevent spam from reaching their destination. Naïve Bayesian algorithm is one of the most effective approaches used in filtering te...
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ژورنال
عنوان ژورنال: Hans Journal of Data Mining
سال: 2012
ISSN: 2163-145X,2163-1468
DOI: 10.12677/hjdm.2012.22004