Machine learning approaches to IoT security: A systematic literature review
With the continuous expansion and evolution of IoT applications, attacks on those IoT
applications continue to grow rapidly. In this systematic literature review (SLR) paper, our …
applications continue to grow rapidly. In this systematic literature review (SLR) paper, our …
A systematic survey of data mining and big data analysis in internet of things
Y Zhong, L Chen, C Dan, A Rezaeipanah - The Journal of …, 2022 - Springer
Abstract The Internet of Things (IoT) is an emerging paradigm that offers remarkable
opportunities for data mining and analysis. IoT envisions a world where all smartphones …
opportunities for data mining and analysis. IoT envisions a world where all smartphones …
Towards the development of a realistic multidimensional IoT profiling dataset
The Internet of Things (IoT) is an emerging technology that enables the development of low-
cost and energy-efficient IoT devices across various solutions from smart cities to healthcare …
cost and energy-efficient IoT devices across various solutions from smart cities to healthcare …
Review of artificial intelligence for enhancing intrusion detection in the internet of things
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 …
expansion of adopting IoT-based approaches, their security represents a growing challenge …
A survey on botnets: Incentives, evolution, detection and current trends
SN Thanh Vu, M Stege, PI El-Habr, J Bang, N Dragoni - Future Internet, 2021 - mdpi.com
Botnets, groups of malware-infected hosts controlled by malicious actors, have gained
prominence in an era of pervasive computing and the Internet of Things. Botnets have …
prominence in an era of pervasive computing and the Internet of Things. Botnets have …
[HTML][HTML] A genomic rule-based KNN model for fast flux botnet detection
Abstract Fast Flux Botnet (FFB) is an advance method developed by cyber criminals to
perpetrate distributed malicious attacks. The major problems of existing FFB detection …
perpetrate distributed malicious attacks. The major problems of existing FFB detection …
Unveiling malicious DNS behavior profiling and generating benchmark dataset through application layer traffic analysis
Abstract The Domain Name System (DNS) is a prime target for cyber attacks, necessitating
the monitoring and analysis of DNS activities to detect malicious behaviors. This paper …
the monitoring and analysis of DNS activities to detect malicious behaviors. This paper …
A survey of using machine learning in IoT security and the challenges faced by researchers
KM Harahsheh, CH Chen - Informatica, 2023 - digitalcommons.odu.edu
Abstract The Internet of Things (IoT) has become more popular in the last 15 years as it has
significantly improved and gained control in multiple fields. We are nowadays surrounded by …
significantly improved and gained control in multiple fields. We are nowadays surrounded by …
The use of honeypot in machine learning based on malware detection: A review
IMM Matin, B Rahardjo - … Conference on Cyber and IT Service …, 2020 - ieeexplore.ieee.org
A very significant increase in the spread of malware has resulted in malware analysis using
signature matching approaches and heuristic methods that are no longer suitable for …
signature matching approaches and heuristic methods that are no longer suitable for …
A comparative analysis of using ensemble trees for botnet detection and classification in IoT
Enhancing IoT security is a corner stone for building trust in its technology and driving its
growth. Limited resources and diversified nature of IoT devices make them vulnerable to …
growth. Limited resources and diversified nature of IoT devices make them vulnerable to …