Research on Spam Message Identification Based on Big Data Summary: Spam message detection and analyses Design and implementation of accurate spam identification and filtering system based on big data technology
Abstrak
With the rapid development of the mobile Internet, mobile phone SMS has become an essential means of contact in people's daily life and has been widely used in various fields by virtue of its advantages such as low price, convenient use and reliable delivery. However, the massive use of SMS has brought certain hidden dangers in terms of information security, such as the proliferation of spam SMS. Because of this, how to maintain the healthy development of the SMS business while avoiding the adverse effects caused by spam has become an urgent problem to be solved. First, extract text keywords as labels through SMS text segmentation, and classify and process the labels; second, from the spam SMS dataset, obtain the label classification combinations of spam SMS to generate a new dataset; then, build a model based on convolutional neural network and recurrent neural network, conduct recognition training on the new dataset, and generate a scoring algorithm; finally, build a big data platform to distributed processing a large amount of data to meet the actual enterprise needs.
Penulis (2)
Guang-zhen Wu
Yang Liu
Format Sitasi
Akses Cepat
- Tahun Terbit
- 2025
- Bahasa
- en
- Sumber Database
- Semantic Scholar
- DOI
- 10.1145/3727505.3727506
- Akses
- Open Access ✓