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 …

[HTML][HTML] Detecting cybersecurity attacks in internet of things using artificial intelligence methods: A systematic literature review

M Abdullahi, Y Baashar, H Alhussian, A Alwadain… - Electronics, 2022 - mdpi.com
In recent years, technology has advanced to the fourth industrial revolution (Industry 4.0),
where the Internet of things (IoTs), fog computing, computer security, and cyberattacks have …

Ransomware: Recent advances, analysis, challenges and future research directions

C Beaman, A Barkworth, TD Akande, S Hakak… - Computers & …, 2021 - Elsevier
The COVID-19 pandemic has witnessed a huge surge in the number of ransomware attacks.
Different institutions such as healthcare, financial, and government have been targeted …

A comprehensive survey on machine learning approaches for malware detection in IoT-based enterprise information system

A Gaurav, BB Gupta, PK Panigrahi - Enterprise Information …, 2023 - Taylor & Francis
ABSTRACT The Internet of Things (IoT) is a relatively new technology that has piqued
academics' and business information systems' attention in recent years. The Internet of …

A comprehensive review on malware detection approaches

ÖA Aslan, R Samet - IEEE access, 2020 - ieeexplore.ieee.org
According to the recent studies, malicious software (malware) is increasing at an alarming
rate, and some malware can hide in the system by using different obfuscation techniques. In …

A survey on ransomware: Evolution, taxonomy, and defense solutions

H Oz, A Aris, A Levi, AS Uluagac - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
In recent years, ransomware has been one of the most notorious malware targeting end-
users, governments, and business organizations. It has become a very profitable business …

Image-Based malware classification using ensemble of CNN architectures (IMCEC)

D Vasan, M Alazab, S Wassan, B Safaei, Q Zheng - Computers & Security, 2020 - Elsevier
Both researchers and malware authors have demonstrated that malware scanners are
unfortunately limited and are easily evaded by simple obfuscation techniques. This paper …

An energy-efficient SDN controller architecture for IoT networks with blockchain-based security

A Yazdinejad, RM Parizi… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Internet of Things (IoT) is a disruptive technology in many aspects of our society, ranging
from communications to financial transactions to national security (eg, Internet of …

A deep and scalable unsupervised machine learning system for cyber-attack detection in large-scale smart grids

H Karimipour, A Dehghantanha, RM Parizi… - Ieee …, 2019 - ieeexplore.ieee.org
Smart grid technology increases reliability, security, and efficiency of the electrical grids.
However, its strong dependencies on digital communication technology bring up new …

A deep recurrent neural network based approach for internet of things malware threat hunting

H HaddadPajouh, A Dehghantanha, R Khayami… - Future Generation …, 2018 - Elsevier
Abstract Internet of Things (IoT) devices are increasingly deployed in different industries and
for different purposes (eg sensing/collecting of environmental data in both civilian and …