Neural Network Model for Email-Spam Detection
ثبت نشده
چکیده
Email spam is a word that we come across in our daily life. The word spam means junk mails. The unsolicited emails that are received by any person in his/her mailbox are called spam. These junk mails are usually sent in bulk for advertising and marketing some products. This work presents a neural network approach to intrusion detection. A Multi-Layer Perceptron using Back Propagation Algorithm is used to classify the emails as a spam or normal mail in an email spam application.
منابع مشابه
An Effective Model for SMS Spam Detection Using Content-based Features and Averaged Neural Network
In recent years, there has been considerable interest among people to use short message service (SMS) as one of the essential and straightforward communications services on mobile devices. The increased popularity of this service also increased the number of mobile devices attacks such as SMS spam messages. SMS spam messages constitute a real problem to mobile subscribers; this worries telecomm...
متن کاملA Novel Hybrid Approach for Email Spam Detection based on Scatter Search Algorithm and K-Nearest Neighbors
Because cyberspace and Internet predominate in the life of users, in addition to business opportunities and time reductions, threats like information theft, penetration into systems, etc. are included in the field of hardware and software. Security is the top priority to prevent a cyber-attack that users should initially be detecting the type of attacks because virtual environments are not moni...
متن کاملSpam Detection using Generalized Additive Neural Networks
During the last decade the number of spam messages sent has increased significantly. These undesired emails place a heavy burden on end users and email service providers. As a result, a tenacious struggle to outsmart each other exists between people who send spam and the spam filter providers. Constant innovation is therefore of vital importance to curb the rapid increase of spam. In this artic...
متن کاملA New Hybrid Approach of K-Nearest Neighbors Algorithm with Particle Swarm Optimization for E-Mail Spam Detection
Emails are one of the fastest economic communications. Increasing email users has caused the increase of spam in recent years. As we know, spam not only damages user’s profits, time-consuming and bandwidth, but also has become as a risk to efficiency, reliability, and security of a network. Spam developers are always trying to find ways to escape the existing filters therefore new filters to de...
متن کاملA New Model for Email Spam Detection using Hybrid of Magnetic Optimization Algorithm with Harmony Search Algorithm
Unfortunately, among internet services, users are faced with several unwanted messages that are not even related to their interests and scope, and they contain advertising or even malicious content. Spam email contains a huge collection of infected and malicious advertising emails that harms data destroying and stealing personal information for malicious purposes. In most cases, spam emails con...
متن کامل