Results 51 to 60 of about 1,405 (158)

Visualized Malware Multi-Classification Framework Using Fine-Tuned CNN-Based Transfer Learning Models

Applied Sciences, 2021
There is a massive growth in malicious software (Malware) development, which causes substantial security threats to individuals and organizations. Cybersecurity researchers makes continuous efforts to defend against these malware risks.
Walid El-Shafai, Iman Almomani, Aala AlKhayer   +2 more
doaj   +1 more source

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

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

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

Method of anti-confusion texture feature descriptor for malware images

Tongxin xuebao, 2018
It is a new method that uses image processing and machine learning algorithms to classify malware samples in malware visualization field.The texture feature description method has great influence on the result.To solve this problem,a new method was ...
Yashu LIU, Zhihai WANG, Hanbing YAN, Yueran HOU, Yukun LAI   +4 more
doaj   +2 more sources

Blockchain in Communication Networks: A Comprehensive Review

IET Blockchain, Volume 6, Issue 1, January/December 2026.
This article provides a comprehensive review of blockchain applications in communication networks, focusing on domains such as IoT, 5G, vehicular systems, and decentralised trust infrastructures. It examines key challenges—including scalability, interoperability, and latency—and outlines future directions such as lightweight consensus protocols and AI ...
Quazi Mamun, Zhenni Pan, Jun Wu
wiley   +1 more source

Usability Evaluation of a Push‐Based Passwordless Authentication Model Using Public‐Key Cryptography

IET Biometrics, Volume 2026, Issue 1, 2026.
Despite major advancements in the sphere of the public‐key authentication specifically in the instances of the newly established standards like WebAuthn and the FIDO2, the practical implementation of the passwordless login systems is still hindered by the usability factors, platform‐related requirements, and the very nature of the deployment process is
Ghulam Mustafa, Shah Zaman Nizamani, Irfana Memon, Asif Ali Wagan, Solomiia Fedushko, Abdullah Al Hejaili, M. Srinivas   +6 more
wiley   +1 more source

RMDNet-Deep Learning Paradigms for Effective Malware Detection and Classification

IEEE Access
Malware analysis and detection are still essential for maintaining the security of networks and computer systems, even as the threat landscape shifts.
S. Puneeth, Shyam Lal, Mahendra Pratap Singh, B. S. Raghavendra   +3 more
doaj   +1 more source

Generative Adversarial Network for Global Image-Based Local Image to Improve Malware Classification Using Convolutional Neural Network

Applied Sciences, 2020
Malware detection and classification methods are being actively developed to protect personal information from hackers. Global images of malware (in a program that includes personal information) can be utilized to detect or classify it.
Sejun Jang, Shuyu Li, Yunsick Sung
doaj   +1 more source