Attention-based multidimensional deep learning approach for cross-architecture IoMT malware detection and classification in healthcare cyber-physical systems

V Ravi, TD Pham, M Alazab - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
A literature survey shows that the number of malware attacks is gradually growing over the
years due to the growing trend of Internet of Medical Things (IoMT) devices. To detect and …

Machine learning enabled industrial iot security: Challenges, trends and solutions

C Ni, SC Li - Journal of Industrial Information Integration, 2024 - Elsevier
Abstract Introduction: The increasingly integrated Industrial IoT (IIoT) with industrial systems
brings benefits such as intelligent analytics, predictive maintenance, and remote monitoring …

Deep learning based cross architecture internet of things malware detection and classification

R Chaganti, V Ravi, TD Pham - Computers & Security, 2022 - Elsevier
The number of publicly exposed Internet of Things (IoT) devices has been increasing, as
more number of these devices connected to the internet with default settings. The devices …

Cybersecurity attacks in vehicular sensors

Z El-Rewini, K Sadatsharan, N Sugunaraj… - IEEE Sensors …, 2020 - ieeexplore.ieee.org
Today's modern vehicles contain anywhere from sixty to one-hundred sensors and exhibit
the characteristics of Cyber-Physical-Systems (CPS). There is a high degree of coupling …

Security and privacy issues in autonomous vehicles: A layer-based survey

M Hataba, A Sherif, M Mahmoud… - IEEE Open Journal …, 2022 - ieeexplore.ieee.org
Artificial Intelligence (AI) is changing every technology we are used to deal with. Autonomy
has long been a sought-after goal in vehicles, and now more than ever we are very close to …

Intelligent Mirai malware detection for IoT nodes

TG Palla, S Tayeb - Electronics, 2021 - mdpi.com
The advancement in recent IoT devices has led to catastrophic attacks on the devices
resulting in breaches in user privacy and exhausting resources of various organizations, so …

Categorizing malware via A Word2Vec-based temporal convolutional network scheme

J Sun, X Luo, H Gao, W Wang, Y Gao… - Journal of Cloud …, 2020 - Springer
As edge computing paradigm achieves great popularity in recent years, there remain some
technical challenges that must be addressed to guarantee smart device security in Internet …

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 …

Data-driven malware detection for 6G networks: A survey from the perspective of continuous learning and explainability via visualisation

DT Uysal, PD Yoo, K Taha - IEEE Open Journal of Vehicular …, 2022 - ieeexplore.ieee.org
5G is inherently prone to security vulnerabilities. We witness that many today's networks
contain 5G security flaws due to their reliance on the existing 4G network core. A lack of …

Cybersecurity for autonomous vehicles against malware attacks in smart-cities

S Aurangzeb, M Aleem, MT Khan, H Anwar… - Cluster …, 2024 - Springer
Abstract Smart Autonomous Vehicles (AVSs) are networks of Cyber-Physical Systems
(CPSs) in which they wirelessly communicate with other CPSs sub-systems (eg, smart …