Review of artificial intelligence for enhancing intrusion detection in the internet of things

M Saied, S Guirguis, M Madbouly - Engineering Applications of Artificial …, 2024 - Elsevier
Internet of Things is shaping the quality of living standard. With the rapid growth and
expansion of adopting IoT-based approaches, their security represents a growing challenge …

[HTML][HTML] A novel ensemble method for enhancing Internet of Things device security against botnet attacks

A Arshad, M Jabeen, S Ubaid, A Raza… - Decision Analytics …, 2023 - Elsevier
The growing number of connected Internet of Things (IoT) devices has led to the daily
growth of network botnet attacks. The networks of compromised devices controlled by a …

Recursive feature elimination with cross-validation with decision tree: Feature selection method for machine learning-based intrusion detection systems

M Awad, S Fraihat - Journal of Sensor and Actuator Networks, 2023 - mdpi.com
The frequency of cyber-attacks on the Internet of Things (IoT) networks has significantly
increased in recent years. Anomaly-based network intrusion detection systems (NIDSs) offer …

Enhanced botnet detection in IoT networks using zebra optimization and dual-channel GAN classification

SKK Shareef, RK Chaitanya, S Chennupalli… - Scientific Reports, 2024 - nature.com
Abstract The Internet of Things (IoT) permeates various sectors, including healthcare, smart
cities, and agriculture, alongside critical infrastructure management. However, its …

An effective classification of DDoS attacks in a distributed network by adopting hierarchical machine learning and hyperparameters optimization techniques

S Dasari, R Kaluri - IEEE Access, 2024 - ieeexplore.ieee.org
Data privacy is essential in the financial sector to protect client's sensitive information,
prevent financial fraud, ensure regulatory compliance, and safeguard intellectual property. It …

[PDF][PDF] ATTACKS DETECTION IN INTERNET OF THINGS USING MACHINE LEARNING TECHNIQUES: A REVIEW

AAAAD Saleem, AA Abdulrahman - Journal of Applied …, 2024 - researchgate.net
The proliferation of IoT devices across sectors such as home automation, business,
healthcare, and transportation has led to the generation of vast amounts of sensitive data …

A survey on the contribution of ML and DL to the detection and prevention of botnet attacks

Y EL Yamani, Y Baddi, N EL Kamoun - Journal of Reliable Intelligent …, 2024 - Springer
Abstract Machine Learning (ML) and Deep Learning (DL) are transforming the detection and
prevention of botnets, significant threats in cybersecurity. In this survey, we highlight the shift …

Smart approach for botnet detection based on Network Traffic analysis

A Obeidat, R Yaqbeh - Journal of Electrical and Computer …, 2022 - Wiley Online Library
Today, botnets are the most common threat on the Internet and are used as the main attack
vector against individuals and businesses. Cybercriminals have exploited botnets for many …

Detection of botnet in IoT network through machine learning based optimized feature importance via ensemble models

SM din, R Sharma, F Rizvi, N Sharma - International Journal of Information …, 2024 - Springer
The number of cyberattacks has grown along with the expansion of the Internet of Things
(IoT), which necessitates detection of cyberattacks on IoT devices. Different machine …

[PDF][PDF] Towards robust IDSs: An integrated approach of hybrid feature selection and machine learning

M Al-Omari, QA Al-Haija - J. Internet Serv. Inf. Secur, 2024 - jisis.org
Due to the rapid growth of technology, the urgency for effective cybersecurity systems has
become increasingly critical, notably within the paradigm of the Internet of Things (IoT) and …