Results 81 to 90 of about 4,236,332 (208)

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

open access: yesEngineering 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   +6 more
wiley   +1 more source

A machine learning technique for Android malicious attacks detection based on API calls [PDF]

open access: yesDecision Science Letters
Android malware is widespread and it is considered as one of the most threatening attacks recently. The threat is targeting to damage access data or information or leaking them; in general, malicious software consists of viruses, worms, and ...
Mousa AL-Akhras   +3 more
doaj   +1 more source

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

open access: yesSECURITY 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

open access: yesSECURITY 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   +2 more
wiley   +1 more source

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

open access: yesSECURITY 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   +4 more
wiley   +1 more source

Advances in Malware Analysis and Detection in Cloud Computing Environments: A Review

open access: yesInternational Journal of Safety and Security Engineering
Cloud computing, integral for data storage and online services, presents significant advantages over traditional data storage and distribution methods, including enhanced convenience, on-demand storage, scalability, and cost efficiency.
S. M. Rao, Arpit Jain
semanticscholar   +1 more source

Guardians of ICS: A Comparative Analysis of Anomaly Detection Techniques

open access: yesIET Cyber-Physical Systems: Theory &Applications, Volume 11, Issue 1, January/December 2026.
This study presents a comparative evaluation of supervised and unsupervised learning models for anomaly detection in industrial control systems (ICS), using data from the SWaT testbed. Results show that although supervised models offer higher precision, they miss more unknown attacks, whereas unsupervised models achieve better recall but with increased
Zequn Wang   +4 more
wiley   +1 more source

Modeling and Stability Analysis of Malware Propagation in Hierarchically Protected WSNs Based on Epidemiological Theory

open access: yesIET Control Theory &Applications, Volume 20, Issue 1, January/December 2026.
This paper proposes a novel malware propagation model based on epidemiological theory, specifically tailored for hierarchically protected wireless sensor networks (WSNs). We classify nodes into strongly and weakly protected categories and establish a four‐state propagation dynamics model (susceptible, exposed, infected, and recovered) to simulate ...
Xuejin Zhu, Nan Fu
wiley   +1 more source

A comprehensive survey on deep learning based malware detection techniques

open access: yesComputer Science Review, 2023
Gopinath M., S. C. Sethuraman
semanticscholar   +1 more source

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