Results 61 to 70 of about 6,970 (211)

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

Reverse Engineering untuk Analisis Malware Remote Access Trojan

JEPIN (Jurnal Edukasi dan Penelitian Informatika), 2019
Para hacker menggunakan malware Remote Access Trojan untuk merusak sistem kemudian mencuri data para korbannya. Diperlukan analisis mendalam mengenai malware baru-baru ini karena malware dapat berkamuflase seperti sistem tidak dicurigai.
Tesa Pajar Setia, Aldy Putra Aldya, Nur Widiyasono   +2 more
doaj   +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

Guardians of ICS: A Comparative Analysis of Anomaly Detection Techniques

IET 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, Muhammad Azmi Umer, Haibo Zhang, Naveed ul Hassan, Chuadhry Mujeeb Ahmed   +4 more
wiley   +1 more source

Deep Belief Networks-based framework for malware detection in Android systems

Alexandria Engineering Journal, 2018
Malware is the umbrella term that denotes attacking any system by malicious software. During the last few years, the popularity of Android smartphones led to the sneak of several malware applications into different Android markets without any difficulty.
Dina Saif, S.M. El-Gokhy, E. Sallam
doaj   +1 more source

Undecidable problems in malware analysis

2017 12th International Conference for Internet Technology and Secured Transactions (ICITST), 2017
Malware analysis is a challenging task in the theory as well as the practice of computer science. Many important problems in malware analysis have been shown to be undecidable. These problems include virus detection, detecting unpacking execution, matching malware samples against a set of given templates, and detecting trigger-based behavior.
Batur, Berker, Selçuk, Ali Aydın, Orhan, Fatih   +2 more
openaire   +2 more sources

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

IET 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

I-MCM: IoT Malware Counter Measures for Cross-Architecture IoT Malware Detection

IEEE Access
The recent attacks initiated by malware-infected IoT devices illustrate that these attacks have tremendous impacts not only on the targeted systems but also on the entire internet infrastructure.
Ibrahim Gulatas, H. Hakan Kilinc, A. Halim Zaim, M. Ali Aydin   +3 more
doaj   +1 more source