Detection of Social Network Spam Based on Improved Machine Learning
With the aid of several models and information, the machine learning model's spam
message identification has been carried out correctly. In order to provide accurate …
message identification has been carried out correctly. In order to provide accurate …
Optimizing hydrogen evolution prediction: A unified approach using random forests, lightGBM, and Bagging Regressor ensemble model
Hydrogen, as a clean and versatile energy carrier, plays a pivotal role in addressing global
energy challenges and transitioning towards sustainable energy systems. This study …
energy challenges and transitioning towards sustainable energy systems. This study …
A Machine Learning Ensemble Approach for Predicting Solar Sensitive Hybrid Photocatalysts on Hydrogen Evolution
Hydrogen, as the lightest and most abundant element in the universe, has emerged as a
pivotal player in the quest for sustainable energy solutions. Its remarkable properties, such …
pivotal player in the quest for sustainable energy solutions. Its remarkable properties, such …
Empirical enhancement of intrusion detection systems: a comprehensive approach with genetic algorithm-based hyperparameter tuning and hybrid feature selection
Abstract Machine learning-based IDSs have demonstrated promising outcomes in
identifying and mitigating security threats within IoT networks. However, the efficacy of such …
identifying and mitigating security threats within IoT networks. However, the efficacy of such …
State of the art on Twitter spam detection
Extensive use of social networking sites such as Twitter shows their popularity among users.
It attracts normal users as well as illegitimate users. Twitter spam is a serious problem to be …
It attracts normal users as well as illegitimate users. Twitter spam is a serious problem to be …
[PDF][PDF] Critical evaluation on spam content detection in social media
AR Chrismanto, K Sari, Y Suyanto - J. Theor. Appl. Inf. Technol, 2022 - jatit.org
The spam content detection problem is still challenging due to its complexity, feature
extraction process, language, context-aware detection capabilities, performance, and …
extraction process, language, context-aware detection capabilities, performance, and …
Detection of twitter spam using GLoVe vocabulary features, bidirectional LSTM and convolution neural network
Twitter spam is used to describe any form of unwanted or unsolicited communications,
tweets, or activities that users encounter on the social media platform Twitter. This can …
tweets, or activities that users encounter on the social media platform Twitter. This can …
Swift Detection of XSS Attacks: Enhancing XSS Attack Detection by Leveraging Hybrid Semantic Embeddings and AI Techniques
Abstract Cross-Site Scripting (XSS) attacks continue to be a significant threat to web
application security, necessitating robust detection mechanisms to safeguard user data and …
application security, necessitating robust detection mechanisms to safeguard user data and …
VoteDroid: a new ensemble voting classifier for malware detection based on fine-tuned deep learning models
H Bakır - Multimedia Tools and Applications, 2024 - Springer
In this work, VoteDroid a novel fine-tuned deep learning models-based ensemble voting
classifier has been proposed for detecting malicious behavior in Android applications. To …
classifier has been proposed for detecting malicious behavior in Android applications. To …
ALBERT4Spam: A Novel Approach for Spam Detection on Social Networks
Engaging in social media browsing stands out as one of the most prevalent online activities.
As social media increasingly integrates into our daily routines, it opens up numerous …
As social media increasingly integrates into our daily routines, it opens up numerous …