Machine learning-powered encrypted network traffic analysis: A comprehensive survey

M Shen, K Ye, X Liu, L Zhu, J Kang… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Traffic analysis is the process of monitoring network activities, discovering specific patterns,
and gleaning valuable information from network traffic. It can be applied in various fields …

[HTML][HTML] Advancing IoT security: A systematic review of machine learning approaches for the detection of IoT botnets

A Nazir, J He, N Zhu, A Wajahat, X Ma, F Ullah… - Journal of King Saud …, 2023 - Elsevier
Abstract The Internet of Things (IoT) has transformed many aspects of modern life, from
healthcare and transportation to home automation and industrial control systems. However …

A two-fold machine learning approach to prevent and detect IoT botnet attacks

F Hussain, SG Abbas, IM Pires, S Tanveer… - Ieee …, 2021 - ieeexplore.ieee.org
The botnet attack is a multi-stage and the most prevalent cyber-attack in the Internet of
Things (IoT) environment that initiates with scanning activity and ends at the distributed …

[HTML][HTML] Botnet attack detection using local global best bat algorithm for industrial internet of things

A Alharbi, W Alosaimi, H Alyami, HT Rauf… - Electronics, 2021 - mdpi.com
The need for timely identification of Distributed Denial-of-Service (DDoS) attacks in the
Internet of Things (IoT) has become critical in minimizing security risks as the number of IoT …

[HTML][HTML] Artificial intelligence algorithms for malware detection in android-operated mobile devices

H Alkahtani, THH Aldhyani - Sensors, 2022 - mdpi.com
With the rapid expansion of the use of smartphone devices, malicious attacks against
Android mobile devices have increased. The Android system adopted a wide range of …

Advancing network security in industrial IoT: a deep dive into AI-enabled intrusion detection systems

M Shahin, M Maghanaki, A Hosseinzadeh… - Advanced Engineering …, 2024 - Elsevier
The increasing use of Industrial Internet of Things (IIoT) devices has heightened concerns
about cybersecurity threats, particularly botnet attacks. Traditional internet communication …

[PDF][PDF] DNNBoT: Deep neural network-based botnet detection and classification.

MA Haq, MA Rahim Khan - Computers, Materials & Continua, 2022 - academia.edu
The evolution and expansion of IoT devices reduced human efforts, increased resource
utilization, and saved time; however, IoT devices create significant challenges such as lack …

Hybrid machine learning model for efficient botnet attack detection in iot environment

M Ali, M Shahroz, MF Mushtaq, S Alfarhood… - IEEE …, 2024 - ieeexplore.ieee.org
Cyber attacks are growing with the rapid development and wide use of internet technology.
Botnet attack emerged as one of the most harmful attacks. Botnet identification is becoming …

Intelligent techniques for detecting network attacks: review and research directions

M Aljabri, SS Aljameel, RMA Mohammad, SH Almotiri… - Sensors, 2021 - mdpi.com
The significant growth in the use of the Internet and the rapid development of network
technologies are associated with an increased risk of network attacks. Network attacks refer …

[PDF][PDF] A Step Towards Automated Haematology: DL Models for Blood Cell Detection and Classification

IS Rahat, MA Ahmed, D Rohini, A Manjula… - … on Pervasive Health …, 2024 - researchgate.net
INTRODUCTION: Deep Learning has significantly impacted various domains, including
medical imaging and diagnostics, by enabling accurate classification tasks. This research …