A comprehensive survey on deep learning based malware detection techniques

M Gopinath, SC Sethuraman - Computer Science Review, 2023 - Elsevier
Recent theoretical and practical studies have revealed that malware is one of the most
harmful threats to the digital world. Malware mitigation techniques have evolved over the …

A systematic review of data-driven attack detection trends in IoT

S Haque, F El-Moussa, N Komninos, R Muttukrishnan - Sensors, 2023 - mdpi.com
The Internet of Things is perhaps a concept that the world cannot be imagined without today,
having become intertwined in our everyday lives in the domestic, corporate and industrial …

Improving IoT Security With Explainable AI: Quantitative Evaluation of Explainability for IoT Botnet Detection

R Kalakoti, H Bahsi, S Nõmm - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Detecting botnets is an essential task to ensure the security of Internet of Things (IoT)
systems. Machine learning (ML)-based approaches have been widely used for this purpose …

Modeling of botnet detection using chaotic binary Pelican Optimization Algorithm with deep learning on Internet of Things Environment

F Alrowais, MM Eltahir, SS Aljameel, R Marzouk… - IEEE …, 2023 - ieeexplore.ieee.org
Nowadays, there are ample amounts of Internet of Things (IoT) devices interconnected to the
networks, and with technological improvement, cyberattacks and security threads, for …

Machine Learning Approaches for Botnet Detection in Network Traffic

YT Salih, A Fenjan, SR Ahmed, H Ali… - Proceedings of the …, 2024 - dl.acm.org
Botnets pose a significant challenge to network security, continually evolving and
threatening the integrity of digital infrastructure. Traditional botnet detection methodologies …

A Comprehensive Review of Machine Learning Approaches for Detecting Malicious Software.

L Yuanming, R Latih - International Journal on Advanced …, 2024 - search.ebscohost.com
With the continuous development of technology, the types of malware and their variants
continue to increase, which has become an enormous challenge to network security. These …

Enhancing IoT Botnet Attack Detection in SOCs with an Explainable Active Learning Framework

R Kalakoti, S Nõmm, H Bahsi - 2024 IEEE World AI IoT …, 2024 - ieeexplore.ieee.org
The widespread use of Internet of Things (IoT) devices has raised the threat of botnet
attacks, presenting significant challenges for security operations centres (SOCs). While …

Process-aware security monitoring in industrial control systems: A systematic review and future directions

M ur Rehman, H Bahşi - International Journal of Critical Infrastructure …, 2024 - Elsevier
Due to the tight coupling between the cyber and physical components, control systems are
subjected to emerging cyberattacks. In addition to attacks based on networking and …

Machine learning enabled intrusion detection for edge devices in the Internet of Things

M Alsharif, DB Rawat - 2023 IEEE 13th Annual Computing and …, 2023 - ieeexplore.ieee.org
In this paper, we present recent approaches proposed to secure the Internet of Things (IoT)
devices against malicious cyber attacks and malware. As IoT devices have limited …

Class imbalance and concept drift invariant online botnet threat detection framework for heterogeneous IoT edge

A Nitish, J Hanumanthappa, SPS Prakash… - Computers & Security, 2024 - Elsevier
Heterogeneous networks (HetIoT) of high-capacity and resource-constrained IoT devices
and their edge associations for on-device distributed critical workloads—called the edge-of …