A comprehensive survey for intelligent spam email detection

A Karim, S Azam, B Shanmugam, K Kannoorpatti… - Ieee …, 2019 - ieeexplore.ieee.org
The tremendously growing problem of phishing e-mail, also known as spam including spear
phishing or spam borne malware, has demanded a need for reliable intelligent anti-spam e …

Machine learning techniques applied to cybersecurity

J Martínez Torres, C Iglesias Comesaña… - International Journal of …, 2019 - Springer
Abstract Machine learning techniques are a set of mathematical models to solve high non-
linearity problems of different topics: prediction, classification, data association, data …

[HTML][HTML] Improving malicious URLs detection via feature engineering: Linear and nonlinear space transformation methods

T Li, G Kou, Y Peng - Information Systems, 2020 - Elsevier
In malicious URLs detection, traditional classifiers are challenged because the data volume
is huge, patterns are changing over time, and the correlations among features are …

Contributions to the study of SMS spam filtering: new collection and results

TA Almeida, JMG Hidalgo, A Yamakami - … of the 11th ACM symposium on …, 2011 - dl.acm.org
The growth of mobile phone users has lead to a dramatic increasing of SMS spam
messages. In practice, fighting mobile phone spam is difficult by several factors, including …

Spam filtering using a logistic regression model trained by an artificial bee colony algorithm

BK Dedeturk, B Akay - Applied Soft Computing, 2020 - Elsevier
Email spam is a serious problem that annoys recipients and wastes their time. Machine-
learning methods have been prevalent in spam detection systems owing to their efficiency in …

Tubespam: Comment spam filtering on youtube

TC Alberto, JV Lochter… - 2015 IEEE 14th …, 2015 - ieeexplore.ieee.org
The profitability promoted by Google in its brand new video distribution platform YouTube
has attracted an increasing number of users. However, such success has also attracted …

Spam filtering using integrated distribution-based balancing approach and regularized deep neural networks

A Barushka, P Hajek - Applied Intelligence, 2018 - Springer
Rapid growth in the volume of unsolicited and unwanted messages has inspired the
development of many anti-spam methods. Supervised anti-spam filters using machine …

Efficient clustering of emails into spam and ham: The foundational study of a comprehensive unsupervised framework

A Karim, S Azam, B Shanmugam… - IEEE Access, 2020 - ieeexplore.ieee.org
The spread and adoption of spam emails in malicious activities like information and identity
theft, malware propagation, monetary and reputational damage etc. are on the rise with …

Training logistic regression model by enhanced moth flame optimizer for spam email classification

M Salb, L Jovanovic, M Zivkovic, E Tuba… - Computer networks and …, 2022 - Springer
Spam email is a massive issue that bothers and consumes receivers' time and effort.
Because of its effectiveness in identifying mail as wanted or unwanted, machine learning …

Text normalization and semantic indexing to enhance instant messaging and SMS spam filtering

TA Almeida, TP Silva, I Santos, JMG Hidalgo - Knowledge-Based Systems, 2016 - Elsevier
The rapid popularization of smartphones has contributed to the growth of online Instant
Messaging and SMS usage as an alternative way of communication. The increasing number …