Heuristic machine learning approaches for identifying phishing threats across web and email platforms

R Jayaprakash, K Natarajan, JA Daniel… - Frontiers in Artificial …, 2024 - frontiersin.org
Life has become more comfortable in the era of advanced technology in this cutthroat
competitive world. However, there are also emerging harmful technologies that pose a …

GraphTunnel: Robust DNS Tunnel Detection Based on DNS Recursive Resolution Graph

G Gao, W Niu, J Gong, D Gu, S Li… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
DNS tunnels, due to their versatility and concealment, have become a preferred method for
attackers to execute Command and Control (C&C) attacks, posing a significant security …

DNS flooding attack detection scheme through Machine Learning

A El Attar, R Khatoun, F Chbib… - 2024 International …, 2024 - ieeexplore.ieee.org
Domain Name System (DNS) servers are considered registers that enable internet devices
to quickly look up specific web servers and access web pages. DNS flooding is a type of …

Distributed denial-of-service attack detection short review: issues, challenges, and recommendations

AKMA Habib, A Imtiaz, D Tripura, MO Faruk… - Bulletin of Electrical …, 2025 - beei.org
An attacker can attack a network in several methods when there are a lot of device
connections. Distributed denial-of-service (DDoS) attacks could result from this …

Real-time Threat Detection Strategies for Resource-constrained Devices

M Hamidouche, BF Demissie, B Cherif - arXiv preprint arXiv:2403.15078, 2024 - arxiv.org
As more devices connect to the internet, it becomes crucial to address their limitations and
basic security needs. While much research focuses on utilizing ML and DL to tackle security …

Análisis integral de los sistemas de detección de intrusos y sus algoritmos asociados en la seguridad de la información

JRE Suárez, JEP Rodriguez… - INGENIERÍA …, 2023 - 161.132.207.136
El estudio se enfoca principalmente en el análisis y la comparación de las técnicas de
detección de intrusiones en entornos de red, con el objetivo de evaluar el impacto de los …

Exploring Machine Learning's Role in Intrusion Detection Systems for Network Security

PR Rege, A Kalnawat, A Dhablia… - … on Emerging Smart …, 2024 - ieeexplore.ieee.org
The proliferation of network-based services has resulted in an expanded threat landscape
within the domain of cybersecurity. In the realm of network security, Intrusion Detection …

Zero-Day Malware Classification and Detection Using Machine Learning

J Kumar, B Rajendran, SD Sudarsan - SN Computer Science, 2023 - Springer
A zero-day vulnerability is a weakness of the computer software and hardware that has yet
to be discovered by people who might be interested in fixing it. Hackers may use these …

A New Method to Detect Malicious DNS over HTTPS via Feature Reduction

AK Bozkurt, BS Sarıkaya, HE Aköz… - 2024 9th …, 2024 - ieeexplore.ieee.org
The classification of malicious D NS o ver HTTPS (DoH) as malicious or benign is a
challenging task due to its encrypted nature and massive amount of data that needs to be …

Augmenting DNS-Based Security with NetFlow

KS Tharayil, P Kintis… - 2024 4th International …, 2024 - ieeexplore.ieee.org
As cyber threats become more advanced and prevalent, network operators use a variety of
tools and techniques to detect and defend against these attacks. Due to the importance of …