Results 41 to 50 of about 6,970 (211)

Graph neural network‐based attack prediction for communication‐based train control systems

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract The Advanced Persistent Threats (APTs) have emerged as one of the key security challenges to industrial control systems. APTs are complex multi‐step attacks, and they are naturally diverse and complex. Therefore, it is important to comprehend the behaviour of APT attackers and anticipate the upcoming attack actions.
Junyi Zhao, Tao Tang, Bing Bu, Qichang Li   +3 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

Information systems and digitization of traditional knowledge: Trends in cultural heritage and memory institutions and the WIPO Genetic Resources Treaty*

The Journal of World Intellectual Property, EarlyView.
Abstract Understanding the role of information communication technologies (ICTs) in development, especially in relation to marginalized populations, has been the focus of many related disciplinary categories within the broader ecosystem of information sciences.
Chidi Oguamanam
wiley   +1 more source

Retracted: Analysis of Malware Detection and Signature Generation Using a Novel Hybrid Approach [PDF]

, 2023
Mathematical Problems in Engineering
openalex   +1 more source

Securing the Unseen: A Comprehensive Exploration Review of AI‐Powered Models for Zero‐Day Attack Detection

Expert Systems, Volume 43, Issue 3, March 2026.
ABSTRACT Zero‐day exploits remain challenging to detect because they often appear in unknown distributions of signatures and rules. The article entails a systematic review and cross‐sectional synthesis of four fundamental model families for identifying zero‐day intrusions, namely, convolutional neural networks (CNN), deep neural networks (DNN ...
Abdullah Al Siam, Nuruzzaman Faruqui, Akm Azad, Mohammad Ali Moni   +3 more
wiley   +1 more source

MalGraphIQ: A tool for generating behavior representations of malware execution traces

SoftwareX
Understanding and interpreting malware behavior remains an open challenge in the field of cybersecurity. The dynamic analysis of malware execution traces has emerged as a promising approach for discovering behavioral insights that allow the visual ...
Razvan Raducu, Ricardo J. Rodríguez, Pedro Álvarez   +2 more
doaj   +1 more source

A cybersecurity risk analysis framework for systems with artificial intelligence components

International Transactions in Operational Research, Volume 33, Issue 2, Page 798-825, March 2026.
Abstract The introduction of the European Union Artificial Intelligence (AI) Act, the NIST AI Risk Management Framework, and related international norms and policy documents demand a better understanding and implementation of novel risk analysis issues when facing systems with AI components: dealing with new AI‐related impacts; incorporating AI‐based ...
J.M. Camacho, A. Couce‐Vieira, D. Arroyo, D.R. Insua   +3 more
wiley   +1 more source

A Hybrid Framework for Stock Price Forecasting Using Metaheuristic Feature Selection Approaches and Transformer Models Enhanced by Temporal Embedding and Attention Pruning

Applied AI Letters, Volume 7, Issue 1, February 2026.
Workflow of the proposed hybrid BWO‐Transformer framework for stock price prediction. ABSTRACT Accurately predicting stock prices remains a major challenge in financial analytics due to the complexity and noise inherent in market data. Feature selection plays a critical role in improving both computational efficiency and predictive performance. In this
Amirhossein Malakouti Semnani, Sohrab Kordrostami, Amirhossein Refahi Sheikhani, Mohammad Hossein Moattar   +3 more
wiley   +1 more source

Empirical Analysis of Forest Penalizing Attribute and Its Enhanced Variations for Android Malware Detection

Applied Sciences, 2022
As a result of the rapid advancement of mobile and internet technology, a plethora of new mobile security risks has recently emerged. Many techniques have been developed to address the risks associated with Android malware.
Abimbola G. Akintola, Abdullateef O. Balogun, Luiz Fernando Capretz, Hammed A. Mojeed, Shuib Basri, Shakirat A. Salihu, Fatima E. Usman-Hamza, Peter O. Sadiku, Ghaniyyat B. Balogun, Zubair O. Alanamu   +9 more
doaj   +1 more source

The Influence of Big Data‐Driven Educational Technologies on College Teaching Development

Engineering Reports, Volume 8, Issue 2, February 2026.
Exploring the impact of big data on college instructors: enhancing teaching, fostering professional growth, and addressing challenges in data adoption and privacy. ABSTRACT The rapid development of big data and mobile Internet technologies has significantly influenced the instructional growth of college instructors. This study investigated how big data
Ling Yu, Wenye Li, Ying Luo
wiley   +1 more source