Machine Learning for SPAM Detection

P Teja Nallamothu… - Asian Journal of …, 2023 - eprint.subtopublish.com
In practically every industry today, from business to education, emails/messages are used.
Ham and spam are the two subcategories of emails/messages. Email or message spam …

[HTML][HTML] Real-time twitter spam detection and sentiment analysis using machine learning and deep learning techniques

AP Rodrigues, R Fernandes, A Shetty… - Computational …, 2022 - hindawi.com
In this modern world, we are accustomed to a constant stream of data. Major social media
sites like Twitter, Facebook, or Quora face a huge dilemma as a lot of these sites fall victim to …

Spam detection using bidirectional transformers and machine learning classifier algorithms

Y Guo, Z Mustafaoglu… - Journal of Computational …, 2023 - ojs.bonviewpress.com
Spam email has accounted for a high percentage of email traffic and has created problems
worldwide. The deep learning transformer model is an efficient tool in natural language …

Application of natural language processing and machine learning boosted with swarm intelligence for spam email filtering

N Bacanin, M Zivkovic, C Stoean, M Antonijevic… - Mathematics, 2022 - mdpi.com
Spam represents a genuine irritation for email users, since it often disturbs them during their
work or free time. Machine learning approaches are commonly utilized as the engine of …

Email Security Issues, Tools, and Techniques Used in Investigation

E Altulaihan, A Alismail, MM Hafizur Rahman… - Sustainability, 2023 - mdpi.com
The email system is a globally distributed communication infrastructure service that involves
multiple actors playing different roles to ensure end-to-end mail delivery. It is an …

Efficient e-mail spam filtering approach combining Logistic Regression model and Orthogonal Atomic Orbital Search algorithm

G Manita, A Chhabra, O Korbaa - Applied Soft Computing, 2023 - Elsevier
Phishing emails called spam have created a need for reliable and intelligent spam filters.
Machine-learning techniques are effective, but current methods such as Logistic Regression …

[HTML][HTML] The use of artificial intelligence for smart decision-making in smart cities: A moderated mediated model of technology anxiety and internal threats of IoT

A Alloulbi, T Öz, A Alzubi - Mathematical Problems in Engineering, 2022 - hindawi.com
With the rapid development of artificial intelligence (AI), AI for smart decision-making is
attracting a lot of attention, but research on this topic in smart cities is not yet comprehensive …

Addressing feature selection and extreme learning machine tuning by diversity-oriented social network search: an application for phishing websites detection

N Bacanin, M Zivkovic, M Antonijevic… - Complex & Intelligent …, 2023 - Springer
Feature selection and hyper-parameters optimization (tuning) are two of the most important
and challenging tasks in machine learning. To achieve satisfying performance, every …

Hyperparameter optimization of ensemble models for spam email detection

TO Omotehinwa, DO Oyewola - Applied Sciences, 2023 - mdpi.com
Unsolicited emails, popularly referred to as spam, have remained one of the biggest threats
to cybersecurity globally. More than half of the emails sent in 2021 were spam, resulting in …

Email spam detection using hierarchical attention hybrid deep learning method

S Zavrak, S Yilmaz - Expert Systems with Applications, 2023 - Elsevier
Email is one of the most widely used ways to communicate, with millions of people and
businesses relying on it to communicate and share knowledge and information on a daily …