Advancing cybersecurity: a comprehensive review of AI-driven detection techniques

AH Salem, SM Azzam, OE Emam, AA Abohany - Journal of Big Data, 2024 - Springer
As the number and cleverness of cyber-attacks keep increasing rapidly, it's more important
than ever to have good ways to detect and prevent them. Recognizing cyber threats quickly …

Ransomware detection via cosine similarity-based machine learning on bytecode representations

M Argene, C Ravenscroft, I Kingswell - 2024 - authorea.com
Ransomware has become one of the most persistent and damaging threats in the digital
landscape, causing significant disruptions to organizations and individuals worldwide. The …

Machine learning and deep learning techniques for internet of things network anomaly detection—current research trends

SH Rafique, A Abdallah, NS Musa, T Murugan - Sensors, 2024 - mdpi.com
With its exponential growth, the Internet of Things (IoT) has produced unprecedented levels
of connectivity and data. Anomaly detection is a security feature that identifies instances in …

Malware Detection in IoT Devices Using Machine Learning: A Review

D Singh, S Khurana - 2024 International Conference on …, 2024 - ieeexplore.ieee.org
A thorough summary of recent studies on malware detection in Internet of Things
environments can be found in the literature review section. The necessity for complex and …

Examining windows file system irp operations with machine learning for ransomware detection

B Xu, S Wang - 2024 - researchsquare.com
This study introduces an innovative approach to ransomware detection on Windows
operating systems by leveraging Generative Adversarial Networks (GANs) to analyze file …

A Comprehensive Survey on Hardware-Software co-Protection against Invasive, Non-Invasive and Interactive Security Threats

MH Rahman - Cryptology ePrint Archive, 2024 - eprint.iacr.org
In the face of escalating security threats in modern computing systems, there is an urgent
need for comprehensive defense mechanisms that can effectively mitigate invasive …

Proposed Ransomware Detection Model Based on Machine Learning

K Gonza, J Torres, M Curioso, W Ticona - Computer Science On-line …, 2024 - Springer
Ransomware is one of the main malwares that exists today as established by EUROPOL
and Malwarebytes which affects both the international and national context. In this way, the …

Detection and Analysis of Malicious Software Using Machine Learning Models

A Öztürk, S Hızal - Sakarya University Journal of Computer and …, 2024 - saucis.sakarya.edu.tr
The continuous evolution of malware poses a significant challenge in cybersecurity,
adapting to technological advancements despite implemented security measures. This …

Federated Learning-Based Ransomware Detection via Indicators of Compromise

S Koike, H Tanaka, M Maeda - 2024 - researchsquare.com
Ransomware attacks have become increasingly prevalent and sophisticated, posing
significant threats to data security and organizational operations worldwide. Leveraging a …