Results 61 to 70 of about 2,609 (164)

MCPDS: image-based malware classification method using PE metadata alone

Cybersecurity
In response to the increasing threat posed by the exponential growth of malware in cybersecurity, researchers have developed a number of malware classification methods based on malware images and deep learning in recent years.
Yonglin Zhao, Chun Guo, Yuan Ping, Yi Chen, Yunhe Cui, Guowei Shen   +5 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

Classification of Malware Images Using Fine-Tunned ViT

Sakarya University Journal of Computer and Information Sciences
Malware detection and classification have become critical tasks in ensuring the security and integrity of computer systems and networks. Traditional methods of malware analysis often rely on signature-based approaches, which struggle to cope with the ...
Özal Yıldırım, Oğuzhan Katar
doaj   +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, Volume 29, Issue 1, Page 130-161, March 2026.
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

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

Algor‐Ethics in Diabetes Care: Mapping the Route

Diabetes/Metabolism Research and Reviews, Volume 42, Issue 2, February 2026.
ABSTRACT Diabetes mellitus represents a multifaceted global health challenge, frequently coexisting with obesity, cardiovascular complications, and metabolic disorders. Effective management requires individualised, evidence‐based decisions informed by an array of clinical, genetic, and lifestyle data.
Joshua Bemporad, Francesco De Domenico, Paolo Pozzilli   +2 more
wiley   +1 more source

A Machine Learning Framework for Detecting and Preventing Cyber‐Attacks in Industrial Cyber‐Physical Systems

Engineering Reports, Volume 8, Issue 1, January 2026.
Proposed cyber physical system security framework. ABSTRACT The increasing adoption of cyber‐physical systems (CPS) in Industry 4.0 has heightened vulnerability to cyber threats. This study proposes a machine learning–based intrusion detection framework, DBID‐Net, to effectively identify and prevent attacks in CPS environments. The framework integrates
Anurag Sinha, Rejuwan Shamim, Mihika Mahendra, Trupti Mohota, G. Madhukar Rao, Mohammad Nadeem Ahmed, Mohammad Rashid Hussain, Satyam Solanki, Tanish Ranjan, Bhaskar, Mini Kumari, Karan Dixit, Vyom Modi, Syed Immamul Ansarullah, Mohd Asif Shah   +14 more
wiley   +1 more source

Explainable AI With Imbalanced Learning Strategies for Blockchain Transaction Fraud Detection

Engineering Reports, Volume 8, Issue 1, January 2026.
Research methodology pipeline for blockchain fraud detection. ABSTRACT Blockchain networks now support billions of dollars in daily transactions, making reliable and transparent fraud detection essential for maintaining user trust and financial stability.
Ahmed Abbas Jasim Al‐Hchaimi, M. A. Khalifa, Walid El‐Shafai   +2 more
wiley   +1 more source

GRASE: Granulometry Analysis With Semi Eager Classifier to Detect Malware.

International Journal of Interactive Multimedia and Artificial Intelligence
Technological advancement in communication leading to 5G, motivates everyone to get connected to the internet including ‘Devices’, a technology named Web of Things (WoT).
Mahendra Deore, Manoj Tarambale, Jambi Ratna Raja Kumar, Sachin Sakhare   +3 more
doaj   +1 more source

Mi-maml: classifying few-shot advanced malware using multi-improved model-agnostic meta-learning

Cybersecurity
Malware classification has been successful in utilizing machine learning methods. However, it is limited by the reliance on a large number of high-quality labeled datasets and the issue of overfitting. These limitations hinder the accurate classification
Yulong Ji, Kunjin Zou, Bin Zou
doaj   +1 more source