Independent and Personal SMS Spam Filtering

  • Authors:
  • M. Taufiq Nuruzzaman;Changmoo Lee;Deokjai Choi

  • Affiliations:
  • -;-;-

  • Venue:
  • CIT '11 Proceedings of the 2011 IEEE 11th International Conference on Computer and Information Technology
  • Year:
  • 2011

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Abstract

The amount of Short Message Service (SMS) spam is increasing. SMS spam should be put into the spam folder, not the inbox. Some solutions have been proposed that for the most part use Text Classification techniques. However, they need another computer system to create the filtering system using a large amount of SMS data in advance and install the filtering system into the mobile phone to filter incoming SMS. This kind of solution reduces independence because the user has to store received SMS into computer to train or update the filtering system or data and user can get the filtering system. Storing SMS, which may consist of private data especially SMS ham, leads to privacy problem. Obviously, it also increases hardware cost and increases communication cost between mobile phone and computer system. Thus, we propose an independent filtering system that does not need computer system support. The training, filtering and updating processes were done on mobile phone. Our proposed approach filters SMS spam on an independent mobile phone while obtaining reasonable accuracy, minimum storage consumption and acceptable processing time.