Multi-Stage Spam Detection in E-mails via Machine Learning
Dr. Subedha V
, Deebika , Moulika A K , Ms.Tamilselvi K
Multi-Stage Spam Detection in E-mails via Machine Learning
Spam mails or junk mails are usually employed for the purpose of marketing or advertising a product or an organization. Accumulation of spam mails result in the wastage of in-built memory in email applications. Spam mails can be both harmful and harmless. Harmful spam mails might contain malicious links, which on accessing might steal user data whereas harmless spam mails are commonly employed for promotional purposes. Everyday, spam mails are shared in bulk to several email users, irrespective of the content and the language. Considering the problem, this paper has come with the approach of multi-stage spam mail detection methodology that can beapplied to a wide range of spam mails and is implemented using Naïve Bayes Classifier Algorithm.
The multi-stage spam detection system uses different datasets that store spam keywords belonging todifferent languages respectively. Every set of mails pass through four stages of detection, through whichthe junk mails are filtered out.
"Multi-Stage Spam Detection in E-mails via Machine Learning", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.88-92, February-2024, Available :https://tijer.org/TIJER/papers/TIJERB001013.pdf
Volume 11
Issue 2,
February-2024
Pages : 88-92
Paper Reg. ID: TIJER_151156
Published Paper Id: TIJERB001013
Downloads: 000273
Research Area: Science and Technology
Country: Thiruvallur, TamilNadu, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
