Spam is any kind of unwelcome email that you didn't request to receive. However, some spam might be a component of a fraud scheme or an identity theft scam. Although it can be frustrating, not all spam is bad. Anti-spam filters have lately developed into crucial technology for Internet service providers in order to counteract the spam phenomenon's continued rise. Despite the user's curiosity, emails are screened unevenly across different individuals. There isn't a single algorithm for statistically determining if a specific email message is spam or not. We suggest a hybrid method to this problem that combines the Multi objective Genetic Algorithm: Non-dominated Sorting Genetic Algorithm (NSGA-II) with the Navie Bayes spam filtering algorithm, providing a better outcome in minimising spam mails entering the user's mailbox. The name of our suggested hybrid strategy will be SPAM-NSGA-II-NvBys. According to the filter's evaluation, it can make decisions with a high degree of accuracy (96.24 percent in the worst scenario and 99.66 percent in the best case).
Author(s) Details:
S. Kumar,
Builders Engineering College, Tirupur, Tamil Nadu, India.
S .D. Vijayakumar,
Builders Engineering College, Tirupur, Tamil Nadu, India.
R. Praveenkumar,
Builders Engineering College, Tirupur, Tamil Nadu, India.
V. Manimala,
Builders Engineering College, Tirupur, Tamil Nadu, India.
Please see the link here: https://stm.bookpi.org/TAIER-V1/article/view/8189
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