Results 51 to 60 of about 2,945,918 (205)

Ransomware Detection using Process Memory

International Conference on Cyber Warfare and Security, 2022
Ransomware attacks have increased significantly in recent years, causing great destruction and damage to critical systems and business operations. Attackers are unfailingly finding innovative ways to bypass detection mechanisms, which encouraged the adoption of artificial intelligence.
Avinash Singh, Richard Adeyemi Ikuesan, Hein S. Venter   +2 more
openaire   +4 more sources

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

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

Digitalization and Cybersecurity: Firm‐level Evidence

British Journal of Management, EarlyView.
Abstract Digitalization has opposing effects on cybersecurity: While new digital technologies can strengthen security capabilities, they simultaneously expand potential attack surfaces. To determine which effect dominates, we analyse 9606 US firm‐years (2006–2023) with 543 documented breaches and find that increased digitalization, measured through 10 ...
Jukka Sihvonen
wiley   +1 more source

Feature Selection with Random Forest for Ransomware Detection [PDF]

Ransomware continues to be a significant cybersecurity threat, requiring advanced detection techniques to mitigate its impact. In this study, we investigate the effectiveness of feature selection using the Random Forest machine learning algorithm for ...
Institute for Homeland Security
core   +2 more sources

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

Intellectual Property Restitution

The Modern Law Review, EarlyView.
In Europe, open GLAM movements and cultural restitution reforms are overlooking a crucial aspect that should not be underestimated: what should happen to the archival materials, digital collections and intellectual property that are indelibly linked to cultural property.
Andrea Wallace, Mathilde Pavis
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

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