Results 51 to 60 of about 2,768,658 (208)

Ransomware Detection Model Based on Adaptive Graph Neural Network Learning

Applied Sciences
Ransomware is a type of malicious software that encrypts or locks user files and demands a high ransom. It has become a major threat to cyberspace security, especially as it continues to be developed and updated at exponential rates. Ransomware detection
Jun Li, Gengyu Yang, Yanhua Shao
doaj   +1 more source

The Effect of the Ransomware Dataset Age on the Detection Accuracy of Machine Learning Models

Information, 2023
Several supervised machine learning models have been proposed and used to detect Android ransomware. These models were trained using different datasets from different sources.
Qussai M. Yaseen
doaj   +1 more source

Data privacy model using blockchain reinforcement federated learning approach for scalable internet of medical things

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Internet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help ...
Chandramohan Dhasaratha, Mohammad Kamrul Hasan, Shayla Islam, Shailesh Khapre, Salwani Abdullah, Taher M. Ghazal, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Nguyen Vo, Md Akhtaruzzaman   +9 more
wiley   +1 more source

Ransomware deployment methods and analysis: views from a predictive model and human responses

Crime Science, 2019
Ransomware incidents have increased dramatically in the past few years. The number of ransomware variants is also increasing, which means signature and heuristic-based detection techniques are becoming harder to achieve, due to the ever changing pattern ...
Gavin Hull, Henna John, Budi Arief
doaj   +1 more source

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma, Ashutosh Sharma, Alexey Tselykh, Alexander Bozhenyuk, Byung‐Gyu Kim   +4 more
wiley   +1 more source

Western Balkans as the Frontline of Russian Hybrid Warfare

Global Policy, EarlyView.
ABSTRACT Hybrid warfare (HW) scholarship acknowledges the phenomenon's contextual and temporal specificity, yet its dominant conceptual framing has generated a literature largely centred on identifying and categorising hybrid activities. This focus has left the contextual vulnerabilities that enable hybrid threats (HTs) and shape an adversary's ...
Vesna Bojicic‐Dzelilovic
wiley   +1 more source

Never Mind the Bollards: Exploring the Role of GCHQ, MI5, and the National Technical Authorities in UK Security Markets

The Howard Journal of Crime and Justice, EarlyView.
ABSTRACT The cultures and governance of security markets in the United Kingdom are often characterised through a paradoxical narrative of simultaneous state retreat and progressive advance. In the face of repeated recent high‐profile security failures, and global changes in material political economy, we argue that UK security governance is adapting to
Ben Collier, Jamie Buchan
wiley   +1 more source

A Wide and Weighted Deep Ensemble Model for Behavioral Drifting Ransomware Attacks

Mathematics
Ransomware is a type of malware that leverages encryption to execute its attacks. Its continuous evolution underscores its dynamic and ever-changing nature.
Umara Urooj, Bander Ali Saleh Al-rimy, Mazen Gazzan, Anazida Zainal, Eslam Amer, Mohammed Almutairi, Stavros Shiaeles, Frederick Sheldon   +7 more
doaj   +1 more source

Regulating critical technologies: National security and intellectual property

The Journal of World Intellectual Property, EarlyView.
Abstract In recent years, claims of ‘national security’ have surged internationally to protect various security interests including public health, economic security and cybersecurity. National industrial strategies for building critical technologies challenge the scope of ‘national security’ in international intellectual property (IP) protection ...
Phoebe Li, Atilla Kasap
wiley   +1 more source

Leveraging Machine Learning for Ransomware Detection

CoRR, 2022
The current pandemic situation has increased cyber-attacks drastically worldwide. The attackers are using malware like trojans, spyware, rootkits, worms, ransomware heavily. Ransomware is the most notorious malware, yet we did not have any defensive mechanism to prevent or detect a zero-day attack. Most defensive products in the industry rely on either
Nanda Rani, Sunita Vikrant Dhavale
openaire   +2 more sources