Results 61 to 70 of about 36,905 (167)

Extending Memory-Based Obfuscated Malware Detection With Network Behavior

IEEE Open Journal of the Communications Society
Obfuscated and fileless malware families evade traditional detection systems by residing exclusively in memory and employing stealthy techniques such as process injection and encrypted communication.
Jhon F. Mercado, Josue Genaro Almaraz-Rivera, Sergio Armando Gutierrez, Jesus Arturo Perez-Diaz, Luis A. Fletscher, Jose Antonio Cantoral-Ceballos, Juan Felipe Botero   +6 more
doaj   +1 more source

Accelerated‐USE: A Benchmark Framework for GPU‐Driven Graph Neural Network Training

Concurrency and Computation: Practice and Experience, Volume 38, Issue 9, May 2026.
ABSTRACT Graph processing is used in many domains to extract knowledge from real‐world data. With the rise of deep neural networks and scaled compute infrastructure in artificial intelligence (AI), specialized techniques emerged to leverage graphs in applications such as recommendation systems and social networks.
Lucas de Angelo Martins Ribeiro, Willian Borges de Lemos, Vanessa Telles da Silva, Marcelo de Gomensoro Malheiros, Nelson Lopes Duarte Filho, Marcelo Rita Pias   +5 more
wiley   +1 more source

Automatic Detection of Malware-Generated Domains with Recurrent Neural Models [PDF]

, 2017
Modern malware families often rely on domain-generation algorithms (DGAs) to determine rendezvous points to their command-and-control server. Traditional defence strategies (such as blacklisting domains or IP addresses) are inadequate against such ...
Lison, Pierre, Mavroeidis, Vasileios
core   +2 more sources

CAR‐T Cells: Current Status, Challenges, and Future Prospects

MedComm, Volume 7, Issue 5, May 2026.
This graphical abstract outlines the current status, challenges, and future prospects of CAR‐T cells. The biological basis of CAR‐T cell therapy is the elegant redirection of adaptive immunity. Its initial successes have exposed a landscape of multifaceted challenges.
Aya Sedky Adly, Guillaume Cartron, Afnan Sedky Adly, Jean‐Christophe Egea, Pierre‐Yves Collart Dutilleul, Mahmoud Sedky Adly, Martin Villalba   +6 more
wiley   +1 more source

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

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

Electromagnetic Security Vulnerabilities and Instruction Disassembly of Controller in Adaptive Controllers [PDF]

Journal of Systemics, Cybernetics and Informatics, 2021
A controller in adaptive control theory is a critical part in mission critical applications in military and computer-controlled systems. An ability to identify and follow the binary instruction execution in the controller part enables fault ...
Varghese Mathew Vaidyan, Akhilesh Tyagi
doaj  

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

Diverse protection systems for improving security: a study with AntiVirus engines [PDF]

Diverse “barriers” or “protection systems” are very common in many industries, especially in safety-critical ones where the designers must use “defense in depth” techniques to prevent safety failures.
Bishop, P. G., Bloomfield, R. E., Gashi, I., Stankovic, V.   +3 more
core  

A Holistic Intelligent Cryptojacking Malware Detection System

IEEE Access
Recent statistics indicate a continuous rise in cryptojacking malware. This malware covertly exploits users’ device resources to mine cryptocurrencies, such as Bitcoin, without their knowledge or consent.
Hadeel A. Almurshid, Iman Almomani, M. A. Khalifa, Walid El-Shafai   +3 more
doaj   +1 more source