A survey: contribution of ML & DL to the detection & 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 …

DL-ADS: Improved Grey Wolf Optimization Enabled AE-LSTM Technique for Efficient Network Anomaly Detection in Internet of Thing Edge computing

J Manokaran, G Vairavel - IEEE Access, 2024 - ieeexplore.ieee.org
The Internet of Things (IoT) technology has begun to proliferate in recent years, which
simultaneously increases the number of attacks. Owing to the massive volume and multi …

Hybrid Data-Driven Learning-Based Internet of Things Network Intrusion Detection Model

OA Alimi - 2024 IEEE World AI IoT Congress (AIIoT), 2024 - ieeexplore.ieee.org
Early and effective intrusion detection plays a significant role in protecting the privacy within
and between the different physical devices and entities that are interconnected in Internet of …

Cyber Security Intrusion Detection and Bot Data Collection using Deep Learning in the IoT.

FA Alotaibi, S Mishra - International Journal of Advanced …, 2024 - search.ebscohost.com
In the digital age, cybersecurity is a growing concern, especially as IoT continues to grow
rapidly. Cybersecurity intrusion detection systems are critical in protecting IoT environments …

[PDF][PDF] A27-Exploring machine learning approaches for IoT botnet detection

A Rasool - Research Student Conference Tuesday 16–Thursday … - wlv.openrepository.com
Network security plays an important role in Internet of Things (IoT) security. The botnet attack
is one of the challenges that has attracted the attention of experts in this domain in recent …