A fine-grained system driven of attacks over several new representation techniques using machine learning

MA Al Ghamdi - IEEE Access, 2023‏ - ieeexplore.ieee.org
Machine Learning (ML) techniques, especially deep learning, are crucial to many
contemporary real world systems that use Computational Intelligence (CI) as their core …

Hybridization of synergistic swarm and differential evolution with graph convolutional network for distributed denial of service detection and mitigation in IoT …

CR Babu, M Suneetha, MA Ahmed, PR Babu… - Scientific Reports, 2024‏ - nature.com
Enhanced technologies of the future are gradually improving the digital landscape. Internet
of Things (IoT) technology is an advanced technique that is quickly increasing owing to the …

Analyze textual data: deep neural network for adversarial inversion attack in wireless networks

MA Al Ghamdi - SN Applied Sciences, 2023‏ - Springer
Deep neural networks (DNN) are highly effective in a number of tasks related to machine
learning across different domains. It is quite challenging to apply the information gained to …

LLaMa Assisted Reverse Engineering of Modern Ransomware: A Comparative Analysis with Early Crypto-Ransomware

FE Vasconcelos, GS Almeida - 2023‏ - researchsquare.com
The evolution of ransomware from crypto-ransomware to sophisticated data theft
ransomware presents new challenges in cybersecurity. This study investigates the strategic …

Mitigating data exfiltration ransomware through advanced decoy file strategies

S Liu, X Chen - 2023‏ - researchsquare.com
This study introduces an advanced decoy file strategy utilizing Generative Adversarial
Networks (GANs) to combat data exfiltration ransomware threats. Focused on creating highly …

A Study on the Multi-Cyber Range Application of Mission-Based Cybersecurity Testing and Evaluation in Association with the Risk Management Framework

I Kim, M Park, HJ Lee, J Jang, S Lee, D Shin - Information, 2023‏ - mdpi.com
With the advancement of IT technology, intelligent devices such as autonomous vehicles,
unmanned equipment, and drones are rapidly evolving. Consequently, the proliferation of …

Multiple instance learning method based on convolutional neural network and self-attention for early cancer detection

J Liu, S Zhou, M Zang, C Liu, T Liu… - Computer Methods in …, 2024‏ - Taylor & Francis
Early cancer detection using T-cell receptor sequencing (TCR-seq) and multiple instances
learning methods has shown significant effectiveness. We introduce a multiple instance …

Analyzing Data Theft Ransomware Traffic Patterns Using BERT

G Almeida, F Vasconcelos - 2023‏ - preprints.org
This research looks into the evolving dynamics of ransomware, shifting from conventional
encryption-based attacks to sophisticated data exfiltration strategies. Employing the …

Laundry Cluster Management Using Cloud

M Salach, B Trybus, B Pawłowicz… - 2023 18th Conference …, 2023‏ - ieeexplore.ieee.org
Electronic devices in the 21st century have numerous network components, including
wireless or wired Internet access modules. Connecting devices to networks and cloud …

[PDF][PDF] Integrating Ebola optimization search algorithm for enhanced deep learning-based ransomware detection in Internet of Things security

IR Alzahrani, R Allafi - AIMS Mathematics, 2024‏ - aimspress.com
Integrating Ebola optimization search algorithm for enhanced deep learning-based ransomware
detection in Internet of Things secu Page 1 AIMS Mathematics, 9(3): 6784–6802. DOI …