Results 71 to 80 of about 32,608 (204)
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 +4 more
wiley +1 more source
Malware's Impact on e-Business & m-Commerce: they mean business! [PDF]
, 2009 Malware is a dominant issue in the e-Business arena. It is affecting many of the key e-Business actors from the end users, to businesses offering online services to intermediaries and critical essential infrastructure needed to ensure continued e ...
Fung, C.C., Pan, J.Y.
core
Survey on Visualization of Information Diffusion over Networks
Computer Graphics Forum, EarlyView.Abstract Information Diffusion (ID) describes how a value (e.g., a pathogen, a rumor, a packet) spreads through an underlying “medium” network of elements (e.g., a social or computer network). Understanding the information diffusion process is essential to predicting trends, controlling misinformation, and enhancing decision‐making as well as ...
T. Baumgartl +8 more
wiley +1 more source
Detecting and combating Malware [PDF]
, 2011 This master thesis observes a process improvement on detecting Malware, although new methods for combating malware have been developed, it is still difficult to communicate and share useful information garnered through these techniques without ambiguity ...
Kingsley Ezechi, Azuama
core
AFAgarap/malware-classification v0.1-alpha
, 2017 <p>Code implementation of "Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine (SVM) for Malware Classification"</p ...
Abien Fred Agarap
core +1 more source
Applied Sciences, 2020 Traditional malware classification relies on known malware types and significantly large datasets labeled manually which limits its ability to recognize new malware classes.
Zhijie Tang, Peng Wang, Junfeng Wang
doaj +1 more source
Cyberattacks on Small Banks and the Impact on Local Banking Markets
Journal of Money, Credit and Banking, EarlyView.Abstract Cyberattacks on small banks have direct and spillover effects in local markets. Following successful cyberattacks, hacked small banks experience a decline in deposit growth rates. This effect of cyberattacks is not observed in hacked large banks.
FABIAN GOGOLIN +2 more
wiley +1 more source
Efficiency of Machine Learning Methods in Information Security Audit Tasks: A Comparative Analysis
Applied Research, Volume 5, Issue 5, October 2026.Machine learning methods enable accurate identification of processor instruction architectures from byte‐frequency characteristics of executable files. Among the evaluated models, Linear SVC achieved the highest classification performance, demonstrating the potential of AI‐driven approaches for automated information security auditing and digital ...
Z. B. Mukhtarova +5 more
wiley +1 more source
IoT Malware Detection Based on OPCODE Purification
, 2023 Malware threat for Internet of Things (IoT) devices is increasing day by day. The constrained nature of IoT devices makes it impossible to apply high-resource-demand ing anti-malware tools for these devices.
Kılınç, Hacı Hakan +9 more
core +1 more source
Concurrency and Computation: Practice and Experience, Volume 38, Issue 19, October 2026.ABSTRACTThis work presents a privacy‐preserving remote healthcare system that integrates blockchain technology with a root seed‐based pseudonymization mechanism and lightweight cryptographic controls. Addressing the privacy risks of public ledgers and the limited computational resources of medical IoT devices, the proposed system focuses strictly on ...
Hoc Minh Le, Özgür Öksüz
wiley +1 more source