Results 71 to 80 of about 707,343 (186)

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

Exploiting Vision Transformer and Ensemble Learning for Advanced Malware Classification

Engineering Reports, Volume 8, Issue 1, January 2026.
Overview of the proposed RF–ViT ensemble for multi‐class malware classification. Textual (BoW/byte‐frequency) and visual representations are combined via a product rule, achieving improved accuracy and robustness over individual models. ABSTRACT Malware remains a significant concern for modern digital systems, increasing the need for reliable and ...
Fadi Makarem, Rida El Chall, Abed Ellatif Samhat, Khouloud Samrouth, Nader Bakir   +4 more
wiley   +1 more source

Electromagnetic Security Vulnerabilities and Instruction Disassembly of Controller in Adaptive Controllers [PDF]

Journal of Systemics, Cybernetics and Informatics, 2021
A controller in adaptive control theory is a critical part in mission critical applications in military and computer-controlled systems. An ability to identify and follow the binary instruction execution in the controller part enables fault ...
Varghese Mathew Vaidyan, Akhilesh Tyagi
doaj  

SQLi‐ScanEval: A Framework for Design and Evaluation of SQLi Detection Using Vulnerability and Penetration Testing Scanners

Engineering Reports, Volume 8, Issue 1, January 2026.
This paper proposes SQLi‐ScanEval Framework, a standardized SQLi detection system that integrates vulnerability and penetration testing scanners into a standardized framework. It tested seven prominent SQLi vulnerability scanners including OWASP ZAP, Wapiti, Vega, Acunetix, Invicti, Burp Suite, and Arachni on two prominent vulnerable testing ...
Hajira Bashir, Waseem Ullah Khan, Safdar Nawaz Khan Marwat, Shahid Khan, Imran Baig, Yasir Mehmood, Hammad Atta   +6 more
wiley   +1 more source

Malware Detection Using Dual Siamese Network Model

Computer Modeling in Engineering & Sciences
This paper proposes a new approach to counter cyberattacks using the increasingly diverse malware in cyber security. Traditional signature detection methods that utilize static and dynamic features face limitations due to the continuous evolution and ...
ByeongYeol An, JeaHyuk Yang, Seoyeon Kim, Taeguen Kim   +3 more
semanticscholar   +1 more source

A Survey of SIR‐Based Differential Epidemic Models for Control and Security Against Malware Propagation in Computer Networks

SECURITY AND PRIVACY, Volume 9, Issue 1, January/February 2026.
ABSTRACT Unarguably, malware and their variants have metamorphosed into objects of attack and cyber warfare. These issues have directed research focus to modeling infrastructural settings and infection scenarios, analyzing propagation mechanisms, and conducting studies that highlight optimized remedial measures.
Chukwunonso Henry Nwokoye
wiley   +1 more source

Event Log Correlation for Multi‐Step Attack Detection

SECURITY AND PRIVACY, Volume 9, Issue 1, January/February 2026.
ABSTRACT Event log correlation (ELC) is central to detecting multi‐step attacks (MSAD) that unfold across heterogeneous systems and long time horizons. This review synthesises ELC families—mining/sequence, graph learning, provenance/causal correlation, and hybrid LLM‐assisted approaches—through an MSAD‐first lens that ties methods to attack stages and ...
Syed Usman Shaukat, Saad Khan, Simon Parkinson   +2 more
wiley   +1 more source

IEEE 1815.1-Based Power System Security With Bidirectional RNN-Based Network Anomalous Attack Detection for Cyber-Physical System

IEEE Access, 2020
The introduction of the cyber-physical system (CPS) into power systems has created a variety of communication requirements and functions that existing legacy systems do not support.
Sungmoon Kwon, Hyunguk Yoo, Taeshik Shon
doaj   +1 more source

NGMD: next generation malware detection in federated server with deep neural network model for autonomous networks

Scientific Reports
Distributed denial-of-service (DDoS) attacks persistently proliferate, impacting individuals and Internet Service Providers (ISPs). Deep learning (DL) models are paving the way to address these challenges and the dynamic nature of potential threats ...
Himanshi Babbar, S. Rani, Wadii Boulila
semanticscholar   +1 more source

A Hybrid Transformer–CNN Framework for Semantic Behavioral Modeling in Office Malware Detection

SECURITY AND PRIVACY, Volume 9, Issue 1, January/February 2026.
ABSTRACT Office documents have emerged as a prevalent attack vector, with adversaries increasingly embedding executable payloads and malicious macros to evade signature‐based detection mechanisms. To address these challenges, this study presents a hybrid Transformer–CNN semantic behavioral modeling framework for Office malware detection.
Sheikh M. Zeeshan Javed, M. Faisal Amjad, Sajjad A. Ghauri, Shahzaib Tahir, Nauman Anwar Baig   +4 more
wiley   +1 more source