Security and privacy on 6g network edge: A survey

B Mao, J Liu, Y Wu, N Kato - IEEE communications surveys & …, 2023 - ieeexplore.ieee.org
To meet the stringent service requirements of 6G applications such as immersive cloud
eXtended Reality (XR), holographic communication, and digital twin, there is no doubt that …

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 …

A multi-dimensional deep learning framework for iot malware classification and family attribution

M Dib, S Torabi, E Bou-Harb… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The emergence of Internet of Things malware, which leverages exploited IoT devices to
perform large-scale cyber attacks (eg, Mirai botnet), is considered as a major threat to the …

Hybrid deep-learning model to detect botnet attacks over internet of things environments

MY Alzahrani, AM Bamhdi - Soft Computing, 2022 - Springer
In recent years, the use of the internet of things (IoT) has increased dramatically, and
cybersecurity concerns have grown in tandem. Cybersecurity has become a major …

A survey on cross-architectural IoT malware threat hunting

AD Raju, IY Abualhaol, RS Giagone, Y Zhou… - IEEE …, 2021 - ieeexplore.ieee.org
In recent years, the increase in non-Windows malware threats had turned the focus of the
cybersecurity community. Research works on hunting Windows PE-based malwares are …

Unleashing the hidden power of compiler optimization on binary code difference: An empirical study

X Ren, M Ho, J Ming, Y Lei, L Li - Proceedings of the 42nd ACM …, 2021 - dl.acm.org
Hunting binary code difference without source code (ie, binary diffing) has compelling
applications in software security. Due to the high variability of binary code, existing solutions …

Malware threat on edge/fog computing environments from Internet of Things devices perspective

I Gulatas, HH Kilinc, AH Zaim, MA Aydin - IEEE Access, 2023 - ieeexplore.ieee.org
Developing a secure information processing environment highly depends on securing all
the layers and devices in the environment. Edge/Fog computing environments are no …

[HTML][HTML] An empirical study of problems and evaluation of IoT malware classification label sources

T Lei, J Xue, Y Wang, T Baker, Z Niu - Journal of King Saud University …, 2024 - Elsevier
With the proliferation of malware on IoT devices, research on IoT malicious code has also
become more mature. Most studies use learning models to detect or classify malware …

A strings-based similarity analysis approach for characterizing IoT malware and inferring their underlying relationships

S Torabi, M Dib, E Bou-Harb, C Assi… - IEEE Networking …, 2021 - ieeexplore.ieee.org
Mitigating threats associated with the rise of Internet-of-Things (IoT) malware requires
creating a better understanding about the characteristics and inter-relations of IoT malware …

An evolutionary study of IoT malware

H Wang, W Zhang, H He, P Liu, DX Luo… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Recent years have witnessed lots of attacks targeted at the widespread Internet of Things
(IoT) devices and malicious activities conducted by compromised IoT devices. After some …