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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yadav, K. Saha, S.K. Kumaraguru, P. Kumra, R. |
| Copyright Year | 2012 |
| Abstract | Short Message Service (SMS) is one of the most frequently used services in the mobile phones, next to calls. In developing countries like India, SMS is the cheapest mode of communication. The advantage of this fact is exploited by the advertising companies to reach masses. The unsolicited SMS messages (a.k.a. spam SMS) generates notifications, thus consuming precious user attention. To formulate spam SMS problem and understand user's needs and preceptions, we conducted an online survey with 458 participants in different cities of India. Most of the survey participants admitted that they are quite annoyed with burst of SMS spams and in-effectiveness of regulatory solutions. However, some participants reported that, they do get useful information from spam SMSes sometime(e.g. discounts at a popular food joint). In this paper, we present design and implementation of a user-centric spam SMS filtering application i.e. SMSAssassin that uses content based machine learning techniques with user generated features to filter unwanted SMSes and reduces the burden of notifications for a mobile user. |
| Starting Page | 352 |
| Ending Page | 355 |
| File Size | 458720 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467317962 |
| e-ISBN | 9780769547138 |
| DOI | 10.1109/MDM.2012.54 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-07-23 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Mobile communication Bayesian methods Training Unsolicited electronic mail Smart phones Filtering Usable Security SMS Spam Spam Filtering Machine Learning |
| Content Type | Text |
| Resource Type | Article |
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