Composition of hybrid deep learning model and feature optimization for intrusion detection system
Recently, with the massive growth of IoT devices, the attack surfaces have also intensified.
Thus, cybersecurity has become a critical component to protect organizational boundaries …
Thus, cybersecurity has become a critical component to protect organizational boundaries …
A federated learning framework for cyberattack detection in vehicular sensor networks
Abstract Vehicular Sensor Networks (VSN) introduced a new paradigm for modern
transportation systems by improving traffic management and comfort. However, the …
transportation systems by improving traffic management and comfort. However, the …
A weight optimized deep learning model for cluster based intrusion detection system
S Godala, MS Kumar - Optical and Quantum Electronics, 2023 - Springer
In wireless sensor networks (WSNs), the implemented conventional intrusion detection
frame works need more energy and computation time, which impact the overall WSNs …
frame works need more energy and computation time, which impact the overall WSNs …
Machine learning for wireless sensor networks security: An overview of challenges and issues
Energy and security are major challenges in a wireless sensor network, and they work
oppositely. As security complexity increases, battery drain will increase. Due to the limited …
oppositely. As security complexity increases, battery drain will increase. Due to the limited …
An enhanced intrusion detection model based on improved kNN in WSNs
Aiming at the intrusion detection problem of the wireless sensor network (WSN), considering
the combined characteristics of the wireless sensor network, we consider setting up a …
the combined characteristics of the wireless sensor network, we consider setting up a …
Feature selection for intrusion detection system in a cluster-based heterogeneous wireless sensor network
Wireless sensor network (WSN) has become one of the most promising networking solutions
with exciting new applications for the near future. Notwithstanding the resource constrain of …
with exciting new applications for the near future. Notwithstanding the resource constrain of …
Security Enhancement for Deep Reinforcement Learning-Based Strategy in Energy-Efficient Wireless Sensor Networks
Energy efficiency and security issues are the main concerns in wireless sensor networks
(WSNs) because of limited energy resources and the broadcast nature of wireless …
(WSNs) because of limited energy resources and the broadcast nature of wireless …
A systematic and comprehensive survey of recent advances in intrusion detection systems using machine learning: Deep learning, datasets, and attack taxonomy
Recently, intrusion detection systems (IDS) have become an essential part of most
organisations' security architecture due to the rise in frequency and severity of network …
organisations' security architecture due to the rise in frequency and severity of network …
Detecting cybersecurity attacks using different network features with lightgbm and xgboost learners
CSE-CIC-IDS2018 is an intrusion detection dataset containing roughly 16,000,000 normal
and anomalous instances, with about 17% of these instances representing attack traffic. Our …
and anomalous instances, with about 17% of these instances representing attack traffic. Our …
[PDF][PDF] Deep Learning and Entity Embedding-Based Intrusion Detection Model for Wireless Sensor Networks.
B Almaslukh - Computers, Materials & Continua, 2021 - researchgate.net
Wireless sensor networks (WSNs) are considered promising for applications such as military
surveillance and healthcare. The security of these networks must be ensured in order to …
surveillance and healthcare. The security of these networks must be ensured in order to …