[PDF][PDF] Optimal deep reinforcement learning for intrusion detection in UAVs

V Praveena, A Vijayaraj, P Chinnasamy… - … , Materials & Continua, 2022 - researchgate.net
In recent years, progressive developments have been observed in recent technologies and
the production cost has been continuously decreasing. In such scenario, Internet of Things …

Intrusion detection system using deep learning for in-vehicle security

J Zhang, F Li, H Zhang, R Li, Y Li - Ad Hoc Networks, 2019 - Elsevier
With the development of vehicle intelligence technology, the combination of network and
vehicle becomes inevitable, which brings much convenience to people. At the same time …

[PDF][PDF] Intrusion Detection Systems, Issues, Challenges, and Needs.

M Al-Janabi, MA Ismail, AH Ali - Int. J. Comput. Intell. Syst., 2021 - academia.edu
Intrusion detection systems (IDSs) are one of the promising tools for protecting data and
networks; many classification algorithms, such as neural network (NN), Naive Bayes (NB) …

Classifier performance evaluation for lightweight IDS using fog computing in IoT security

BS Khater, AW Abdul Wahab, MYI Idris, MA Hussain… - Electronics, 2021 - mdpi.com
In this article, a Host-Based Intrusion Detection System (HIDS) using a Modified Vector
Space Representation (MVSR) N-gram and Multilayer Perceptron (MLP) model for securing …

Hybrid algorithm to detect DDoS attacks in VANETs

K Adhikary, S Bhushan, S Kumar, K Dutta - Wireless Personal …, 2020 - Springer
Security and safety are fundamental issues in any wireless network. The problem becomes
serious when the specified network is Vehicular Adhoc Network (VANET). VANET faces …

Intrusion detection of UAVs based on the deep belief network optimized by PSO

X Tan, S Su, Z Zuo, X Guo, X Sun - Sensors, 2019 - mdpi.com
With the rapid development of information technology, the problem of the network security of
unmanned aerial vehicles (UAVs) has become increasingly prominent. In order to solve the …

[PDF][PDF] An Intrusion Detection Model for Wireless Sensor Network Based on Information Gain Ratio and Bagging Algorithm.

RH Dong, HH Yan, QY Zhang - Int. J. Netw. Secur., 2020 - ijns.jalaxy.com.tw
Aiming at the problem that the dimension of the traffic data to be processed in the wireless
sensor network (WSN) intrusion detection method is too high, which leads to the large …

An evolutionary computation based feature selection method for intrusion detection

Y Xue, W Jia, X Zhao, W Pang - Security and Communication …, 2018 - Wiley Online Library
As the important elements of the Internet of Things system, wireless sensor network (WSN)
has gradually become popular in many application fields. However, due to the openness of …

Intrusion detection of wireless sensor networks based on IPSO algorithm and BP neural network

X Lu, D Han, L Duan, Q Tian - International Journal of …, 2020 - inderscienceonline.com
The sensor nodes of wireless sensor networks (WSNs) are deployed to an open and
unsupervised region, and they are vulnerable to various types of attacks. Intrusion detection …

C-shaped split ring resonator type metamaterial antenna design using neural network

M Sağık, M Karaaslan, E Ünal, O Akgöl… - Optical …, 2021 - spiedigitallibrary.org
A C-shaped split ring resonator-based metamaterial (MTM) structure placed on a patch
antenna is proposed. An artificial neural network (ANN) is applied to design and determine …