Design And Implementation Of SMS Fraud Based Interceptor Storm System Prompts

The development of mobile communication technology, changing the way people live. Today, text messaging has become the most prevalent in people’s daily lives as a way to communicate. But with the development of mobile communication services, the use of mobile communications services to send spam messages and bad information phenomenon began. SMS scams are a class of the most serious dangers of spam messages, SMS fraud caused by the large number of violations, has led to an increase in mobile customer complaints, complaints upgrade its harmfulness has caused widespread concern in the communityThe proposed text message reminder system to intercept fraud, fraudulent messages appear in recent years for the calling number is changeable, the called number is random, difficult to identify the content of messages and other new features, the new solution is proposed, and the original focus solutions were proposed to improve the distributed based solutions. The system uses Flume for data collection, and cached to Kafka message queue, Storm get the data from the message queue, through gray, white list filtering, based on counting statistics time window, based on Bayesian text classification, and several other aspects of of fraudulent messages to identify and promptly called user to defraud SMS text message alerts issued. This solution improves the processing performance of the system, and the system has been improved scalability, flexibility, stability, adaptability aspects.In this paper, based on the design and implementation of SMS fraud intercept Storm system prompts for a detailed exposition. These include: SMS fraud tips interception systems development and related technologies Background; From the functional point of interception of SMS fraud alerts system requirements analysis; design and implementation of SMS fraud interception system prompts for a detailed description; describes the test conditions of the system. Finally, the author summarizes the project work during the Masters, and prospects to intercept SMS fraud alerts system were discussed.