Results 81 to 90 of about 46,889 (202)

RogueGPT: Unleashing Jailbreak Prompts on LLMs

Engineering Reports, Volume 8, Issue 4, April 2026.
ABSTRACT Large Language Models (LLMs) have seen a remarkable surge in popularity since the latter part of 2022. These models have become vital in the lives of individuals from varying professions. While some users leverage LLMs for academic or informational purposes, others exploit them for illicit activities.
Arpitha Shivaswaroopa, Vanshika Sood, H. L. Gururaj, J. Shreyas, Fadi Al‐Turjman   +4 more
wiley   +1 more source

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

Decision 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, Saud Alghamdi, Hani Omar, Hazzaa Alshareef   +3 more
doaj   +1 more source

Lightweight and Explainable Early Ransomware Detection Using Dynamic API‐Call Features and Ensemble Machine Learning

Engineering Reports, Volume 8, Issue 4, April 2026.
This study presents a lightweight and explainable ransomware detection framework using dynamic API‐call features and ensemble machine learning. The LightGBM model achieves high accuracy (AUC = 0.9937) with low false positives. SHAP‐based feature importance reveals key API behaviors enabling interpretable, efficient, and deployment‐ready ransomware ...
Zain ul Abideen Khan, Muhammad Abid Mughal, Muhammad Usman Hashmi, Raheem Sarwar, Irfan ul Haq   +4 more
wiley   +1 more source

Malware: Detection and Defense

, 2023
In today’s cyber security landscape, companies are facing increasing pressure to protect their data and systems from malicious attackers. As a result, there has been a significant rise in the number of security solutions that can identify malware. But how do you know if an image file is infected with malware? How can you prevent it from running?
openaire   +3 more sources

AI‐Powered Anomaly Detection for Secure Internet of Things (IoT): Optimising XGBoost and Deep Learning With Bayesian Optimisation

CAAI Transactions on Intelligence Technology, Volume 11, Issue 2, Page 447-463, April 2026.
ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL‐KDD benchmark dataset, this paper presents an improved anomaly detection system that combines an optimised sequential neural network ...
Seong‐O Shim, Lal Hussain, Mohammed A. Alqarni, Faisal S. Alsubaei, Rasha Jamal Atwah   +4 more
wiley   +1 more source

Author Retains Full Rights [PDF]

Software and systems complexity can have a profound impact on information security. Such complexity is not only imposed by the imperative technical challenges of monitored heterogeneous and dynamic (IP and VLAN assignments) network infrastructures, but ...
Ad An, An Early, Early Malware Detection, Giac (gcia Gold Certification, Malware Detection   +4 more
core  

Understanding the Autonomous Electric Vehicle Cyber Threat Landscape: A Focus on Infrastructure, Threats and Ontology‐Based Modelling

Energy Internet, Volume 3, Issue 1, Page 39-51, April 2026.
ABSTRACT The development of autonomous electric vehicles (AEVs) represents the convergence of two simultaneous automotive revolutions: electric vehicles (EVs) and autonomous vehicles (AVs). AVs require sensors, decision‐making systems and actuation systems to achieve autonomous driving, whereas EVs require intelligent management and real‐time ...
Ohud Alsadi, Abdulrahman Almijlad, Trinadh Pamulapati, Rajiv Ranjan, Devki Jha, Tejal Shah   +5 more
wiley   +1 more source

Cybersecurity Assurance for SMEs: A Conceptual Framework Integrating Organizational Culture, Fraud Risk Management and Forensic Accounting

Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l'Administration, Volume 43, Issue 1, March 2026.
ABSTRACT As digitalization accelerates across the global economy, small and medium enterprises (SMEs) face increasing exposure to cybersecurity threats, not due to flaws in external platforms, but because of internal organizational vulnerabilities. This paper presents a conceptual framework that integrates the resource‐based view (RBV) and dynamic ...
Ifedapo Francis Awolowo, Egena Ode, Adenike Abidoye, Oluwaseun Ajao, Olamide Jogunola   +4 more
wiley   +1 more source

Preliminary Evidence of the Association Between Binge Eating and Preeclampsia in Pregnant U.S. Military Active‐Duty Service Women

International Journal of Eating Disorders, Volume 59, Issue 3, Page 588-594, March 2026.
ABSTRACT Objectives Binge eating is the most common disordered eating behavior among pregnant women. This study examined the association of binge‐eating frequency with the presence of a self‐reported current preeclampsia diagnosis in a sample of U.S. military active‐duty Service women. Methods Active‐duty Service women (N = 134), 20–27 weeks gestation,
Ruby Schrag, Jason M. Lavender, Autumn Mains, Stephanie Rioux, Isabel Thorstad, Zoe Sinkford, Victoria Thomas, David A. Klein, Mark Haigney, Marian Tanofsky‐Kraff, Katherine A. Thompson   +10 more
wiley   +1 more source

From Static to AI-Driven Detection: A Comprehensive Review of Obfuscated Malware Techniques

IEEE Access
The frequency of cyber attacks targeting individuals, businesses, and organizations globally has escalated in recent years. The evolution of obfuscated malware, designed to evade detection, has been unprecedented, employing new and sophisticated ...
Saranya Chandran, Sreelakshmi R. Syam, Sriram Sankaran, Tulika Pandey, Krishnashree Achuthan   +4 more
doaj   +1 more source