Harnessing advanced hybrid deep learning model for real-time detection and prevention of man-in-the-middle cyber attacks
Abstract The growing number of connected devices in smart home environments has amplified security risks, particularly from Man-in-the-Middle (MitM) attacks. These attacks allow cybercriminals to intercept and manipulate communication streams between devices, often remaining undetected. Traditional...
Saved in:
Main Authors: | V. Kandasamy, A. Ameelia Roseline |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
|
Series: | Scientific Reports |
Subjects: | |
Online Access: | https://doi.org/10.1038/s41598-025-85547-5 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Preventing man-in-the-middle attacks in DNS through certificate less signature
by: Yang HU, et al.
Published: (2021-12-01) -
Fortifying IoT Infrastructure Using Machine Learning for DDoS Attack within Distributed Computing-based Routing in Networks
by: Sharaf Aldeen Abdulkadhum Abbas, et al.
Published: (2024-06-01) -
Graph Neural Network-Based Approach for Detecting False Data Injection Attacks on Voltage Stability
by: Shahriar Rahman Fahim, et al.
Published: (2025-01-01) -
Achieving resist against DHCP man-in-the-middle attack scheme based on key agreement
by: Zhiqiang YAO, et al.
Published: (2021-08-01) -
Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks
by: Mohammed Almehdhar, et al.
Published: (2024-01-01)