Artificial Intelligence in Cybersecurity: A Comprehensive Review and Future Direction

L Ofusori, T Bokaba, S Mhlongo - Applied Artificial Intelligence, 2024 - Taylor & Francis
As cybercrimes are becoming increasingly complex, it is imperative for cybersecurity
measures to become more robust and sophisticated. The crux lies in extracting patterns or …

Intrusion detection systems for IoT based on bio-inspired and machine learning techniques: a systematic review of the literature

R Saadouni, C Gherbi, Z Aliouat, Y Harbi, A Khacha - Cluster Computing, 2024 - Springer
Recent technological advancements have significantly expanded both networks and data,
thereby introducing new forms of attacks that pose considerable challenges to intrusion …

Crsf: An intrusion detection framework for industrial internet of things based on pretrained cnn2d-rnn and svm

S Li, G Chai, Y Wang, G Zhou, Z Li, D Yu, R Gao - IEEE Access, 2023 - ieeexplore.ieee.org
The traditional support vector machine (SVM) requires manual feature extraction to improve
classification performance and relies on the expressive power of manually extracted …

Hybrid deep learning approach for automatic DoS/DDoS attacks detection in software-defined networks

H Elubeyd, D Yiltas-Kaplan - Applied Sciences, 2023 - mdpi.com
This paper proposes a hybrid deep learning algorithm for detecting and defending against
DoS/DDoS attacks in software-defined networks (SDNs). SDNs are becoming increasingly …

Modified genetic algorithm and fine-tuned long short-term memory network for intrusion detection in the internet of things networks with edge capabilities

YK Saheed, OH Abdulganiyu, TA Tchakoucht - Applied Soft Computing, 2024 - Elsevier
The emergence of smart cities is an example of how new technologies, such as the Internet
of Things (IoT), have facilitated the creation of extensive interconnected and intelligent …

Analisis Algoritma K-Means dan Davies Bouldin Index dalam Mencari Cluster Terbaik Kasus Perceraian di Kabupaten Kuningan

Y Sopyan, AD Lesmana… - Building of Informatics …, 2022 - ejurnal.seminar-id.com
Dalam pernikahan hal yang paling dihindari yaitu sebuah perceraian. Perceraian
merupakan putusnya hubungan suami dan istri yang dilakukan secara sah pada saat …

A novel hybrid autoencoder and modified particle swarm optimization feature selection for intrusion detection in the internet of things network

YK Saheed, AA Usman, FD Sukat… - Frontiers in Computer …, 2023 - frontiersin.org
The Internet of Things (IoT) represents a paradigm shift in which the Internet is connected to
real objects in a range of areas, including home automation, industrial processes, human …

Autoencoder via DCNN and LSTM models for intrusion detection in industrial control systems of critical infrastructures

YK Saheed, S Misra… - 2023 IEEE/ACM 4th …, 2023 - ieeexplore.ieee.org
Industrial Control Systems (ICS) are widely used to carry out the fundamental functions of a
society and are frequently employed in Critical Infrastructures (CIs). Consequently …

GADNN: a revolutionary hybrid deep learning neural network for age and sex determination utilizing cone beam computed tomography images of maxillary and frontal …

O Hamidi, M Afrasiabi, M Namaki - BMC Medical Research Methodology, 2024 - Springer
Introduction The determination of identity factors such as age and sex has gained
significance in both criminal and civil cases. Paranasal sinuses like frontal and maxillary …

Improving network intrusion detection performance: an empirical evaluation using extreme gradient boosting (XGBoost) with recursive feature elimination

GS Fuhnwi, M Revelle, C Izurieta - 2024 IEEE 3rd International …, 2024 - ieeexplore.ieee.org
In cybersecurity, Network Intrusion Detection Systems (NIDS) are essential for identifying
and preventing malicious activity within computer networks. Machine learning algorithms …