Challenges of malware detection in the IoT and a review of artificial immune system approaches

H Alrubayyi, G Goteng, M Jaber, J Kelly - Journal of Sensor and Actuator …, 2021 - mdpi.com
The fast growth of the Internet of Things (IoT) and its diverse applications increase the risk of
cyberattacks, one type of which is malware attacks. Due to the IoT devices' different …

Device-centric firmware malware detection for smart inverters using deep transfer learning

SRB Alvee, BH Ahn, S Ahmad, KT Kim… - 2022 IEEE Design …, 2022 - ieeexplore.ieee.org
Since future power grids are inverter-dominant grids and inverters are getting smarter by
incorporating remote access and seamless firmware update, it is anticipated that malware …

[PDF][PDF] Device-centric ransomware detection using machine learning-based memory forensics for smart inverters

AM Jenkins, B Ahn, A Akash, T Kim - Proc. Eighth Annual Industrial …, 2022 - acsac.org
Ransomware attacks are the fastest-growing form of cyberattacks worldwide. Recently,
ransomware attacks have targeted industrial control systems (ICSs), including power grids …

Mobile Malware Detection: A Comparative Study of Machine Learning Models

S Shaambhavi, M Murale Manohar… - … Conference on Computer …, 2023 - Springer
The need to categorize malware programs that can target any computer system or smaller
device is growing as technology advances. Here in this research paper, we are …

Artificial immune systems for detecting unknown malware in the IoT

H Alrubayyi - 2023 - qmro.qmul.ac.uk
With the expansion of the digital world, the number of the Internet of Things (IoT) devices is
evolving dramatically. IoT devices have limited computational power and small memory …

Quantum Convolutional Neural Network-based Online Malware File Detection for Smart Grid Devices

AR Akash, BH Ahn, A Jenkins, A Khot… - 2023 IEEE Design …, 2023 - ieeexplore.ieee.org
Cybersecurity concerns have arisen due to extensive information exchange among
networked smart grid devices which also employ seamless firmware update. An outstanding …

Evolution of Deep Quantum Learning Models Based on Comprehensive Survey on Effective Malware Identification and Analysis

S Poornima, T Subramanian - Artificial Intelligence, Machine …, 2022 - api.taylorfrancis.com
Nowadays, security threat is the biggest issue faced by IT, private, and government
organizations, since they need more amount of information has to be transferred end to end …