The age of ransomware: A survey on the evolution, taxonomy, and research directions

S Razaulla, C Fachkha, C Markarian… - IEEE …, 2023 - ieeexplore.ieee.org
The proliferation of ransomware has become a significant threat to cybersecurity in recent
years, causing significant financial, reputational, and operational damage to individuals and …

AI-based ransomware detection: A comprehensive review

J Ferdous, R Islam, A Mahboubi, MZ Islam - IEEE Access, 2024 - ieeexplore.ieee.org
Ransomware attacks are becoming increasingly sophisticated, thereby rendering
conventional detection methods less effective. Recognizing this challenge, this study …

[HTML][HTML] Ransomware early detection: A survey

M Cen, F Jiang, X Qin, Q Jiang, R Doss - Computer Networks, 2024 - Elsevier
In recent years, ransomware attacks have exploded globally, and it has become one of the
most significant cyber threats to digital infrastructure. Such attacks have been targeting …

Enhanced Ransomware Detection Techniques using Machine Learning Algorithms

G Usha, P Madhavan, MV Cruz… - … on Computing and …, 2021 - ieeexplore.ieee.org
A challenge that governments, enterprises as well as individuals are constantly facing is the
growing threat of ransomware attacks. Ransomware is a type of malware that encrypts the …

Detection of Ransomware Attack Using Deep Learning

M Jemal, DCT Lo - 2023 IEEE Conference on Dependable and …, 2023 - ieeexplore.ieee.org
The number one threat to the digital world is the exponential increase in ransomware
attacks. Ransomware is malware that prevents victims from accessing their resources by …

Android Malware Detection Using Artificial Intelligence

RK Masele, F Khennou - International Conference on Information and …, 2023 - Springer
Malware poses a significant global cybersecurity challenge, targeting individuals,
businesses, institutions, and nations by compromising sensitive information and causing …

Deep Learning Approaches for Ransomware Detection: Assessing CNN and CNN-LSTM Models using Class Imbalance Methods

H Shwetha, N Vineeth, GR Asha - 2024 2nd International …, 2024 - ieeexplore.ieee.org
Ransomware continues to provide a serious risk to smartphone users by restricting access
to data until a ransom is paid. Traditional malware detection methods, such as statistical …

Malware Analysis Using Machine Learning and Deep Learning

R Gupta, P Kumar, S Rani, A Gupta… - 2023 3rd International …, 2023 - ieeexplore.ieee.org
Malware is a severe danger to everyone from home users to huge corporations. As a result,
it's a popular research topic. Malware fingerprints and activity patterns are analyzed both …

[PDF][PDF] Multiclass Prediction of Diabetic Retinopathy Severity Using Machine Learning Algorithms.

NA Abd Aziz, AM Ali, NTN Nor Azamen… - Malaysian Journal of …, 2024 - medic.upm.edu.my
Introduction: Diabetic retinopathy (DR) is a complication of diabetes mellitus (DM) and a
leading cause of vision loss among adults in Malaysia. The severity of DR is influenced by …

[PDF][PDF] Significance and usage of deep learning in health care systems: diagnosis of lung cancer

PM Bala, S Usharani, GL Roselin… - … Journal of Recent …, 2021 - researchgate.net
The deep learning method for detecting lung disease in thoracic X-rays of the general
population will be verified. Retrospective assessment of a deep learning system with …