Results 81 to 90 of about 97,198 (223)
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 +4 more
wiley +1 more source
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 +6 more
wiley +1 more source
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 +2 more
wiley +1 more source
Can Feature Engineering Help Quantum Machine Learning for Malware Detection? [PDF]
, 2023 Ran Liu +2 more
openalex +1 more source
Applied Sciences, 2020 Traditional malware classification relies on known malware types and significantly large datasets labeled manually which limits its ability to recognize new malware classes.
Zhijie Tang, Peng Wang, Junfeng Wang
doaj +1 more source
A Monte Carlo method for the spread of mobile malware [PDF]
, 2015 A new model for the spread of mobile malware based on proximity (i.e. Bluetooth, ad-hoc WiFi or NFC) is introduced. The spread of malware is analyzed using a Monte Carlo method and the results of the simulation are compared with those from mean field ...
Berretti, Alberto, Ciccarone, Simone
core
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 +4 more
wiley +1 more source
Detecting Malware C&C Communication Traffic Using Artificial Intelligence Techniques
Journal of Cybersecurity and PrivacyBanking malware poses a significant threat to users by infecting their computers and then attempting to perform malicious activities such as surreptitiously stealing confidential information from them.
Mohamed Ali Kazi
doaj +1 more source
DroidPortrait: Android Malware Portrait Construction Based on Multidimensional Behavior Analysis
Applied Sciences, 2020 Recently, security incidents such as sensitive data leakage and video/audio hardware control caused by Android malware have raised severe security issues that threaten Android users, so thus behavior analysis and detection research researches of ...
Xin Su +5 more
doaj +1 more source