Machine learning models for phishing detection from TLS traffic

M Kumar, C Kondaiah, AR Pais, RS Rao - Cluster Computing, 2023 - Springer
Phishing is a fraudulent tactic for attackers to obtain victims personal information, such as
passwords, account details, credit card details, and other sensitive information. Existing anti …

Protective factors for developing cognitive skills against cyberattacks

M Cazares, W Fuertes, R Andrade, I Ortiz-Garcés… - Electronics, 2023 - mdpi.com
Cyberattacks capitalize on human behaviors. The prevalence of cyberattacks surged during
the COVID-19 pandemic, fueled by the increased interconnectivity of individuals on online …

A survey on social network's anomalous behavior detection

L Xing, S Li, Q Zhang, H Wu, H Ma, X Zhang - Complex & Intelligent …, 2024 - Springer
The onset of Web 3.0 has catalyzed the rapid advancement of social networking,
transforming platforms into essential elements deeply embedded within the fabric of daily …

A Machine Learning Approach for Phishing Attack Detection

T Choudhary, S Mhapankar, R Bhddha… - Journal of Artificial …, 2023 - ojs.istp-press.com
Phishing is the easiest method for gathering sensitive information from unwary people.
Phishers seek to get private data including passwords, login information, and bank account …

Optimized Phishing Detection with Recurrent Neural Network and Whale Optimizer Algorithm.

BB Gupta, A Gaurav, RW Attar, V Arya… - Computers …, 2024 - search.ebscohost.com
Phishing attacks present a persistent and evolving threat in the cybersecurity land-scape,
necessitating the development of more sophisticated detection methods. Traditional …

User behavior data analysis and product design optimization algorithm based on deep learning

L Liang, Y Ke - International Journal on Interactive Design and …, 2023 - Springer
In modern society, user behavior data analysis and product design optimization have
become one of the key factors for the success of enterprises. Traditional methods are usually …

ANDE: Detect the Anonymity Web Traffic With Comprehensive Model

YL Deng, T Peng, BC Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The escalating growth of network technology and users poses critical challenges to network
security. This paper introduces ANDE, a novel framework designed to enhance the …

A hybrid dimensionality reduction for network intrusion detection

H Ghani, S Salekzamankhani, B Virdee - Journal of Cybersecurity and …, 2023 - mdpi.com
Due to the wide variety of network services, many different types of protocols exist,
producing various packet features. Some features contain irrelevant and redundant …

A secure mechanism for prevention of vishing attack in banking system

DRD Brabin, S Bojjagani - 2023 International conference on …, 2023 - ieeexplore.ieee.org
A vishing attack is a category of Phishing attack in which the attacker attempts to capture
clandestine information through a phone call or Short Message Service (SMS). These types …

Phishing message detection based on keyword matching

KT Tham, KW Ng, SC Haw - Journal of Telecommunications and …, 2023 - search.informit.org
This paper proposes to use the Naive Bayes-based algorithm for phishing detection,
specifically in spam emails. The paper compares probability-based and frequency-based …