Results 51 to 60 of about 5,992 (166)
Representing Botnet-enabled Cyber-attacks and Botnet-takedowns using Club Theory [PDF]
The literature on botnet-enabled cyber-attacks and the literature on botnet takedowns have progressed independently from each other. In this research, these two literature streams are brought together.
Adegboyega, Olukayode
core +1 more source
Base Semantics—A Novel Approach for Minimizing Malware Detection Rules
ABSTRACT The rapid evolution of malware variants has increasingly undermined traditional signature‐based detection techniques, which are easily evaded through obfuscation and polymorphism that preserve malicious functionality. This challenge is particularly acute in Internet of Things (IoT) environments, where device heterogeneity, resource constraints,
Khizar Hayat +5 more
wiley +1 more source
Fighting fire with fire – a Pre-emptive approach to restore control over IT assets from malware infection [PDF]
Malware is a major threat as they induce multiple risks to infected organizations. Current Anti-Malware solutions meant to keep Malware away are challenged on how to keep the risks at bay effectively. When a Malware manages to penetrate an organization’s
Pan, J.Y.
core
A hybrid quantum kernel support vector machine is proposed to detect network intrusions with NISQ devices. The proposed framework combines classical preprocessing with fidelity‐based quantum feature mapping, achieving enhanced accuracy and robustness against cybersecurity threats and leveraging modern benchmark datasets, offering a glimpse of the ...
Mohammad Rafeek Khan +4 more
wiley +1 more source
Los ciberdelincuentes se centran en la actualidad en sus últimas y más avanzadas armas, llamadas botnet, expresamente enfocadas al ánimo de lucro, por medio de acciones ilegales. Convirtiéndose estos hackers oscuros en cómplices o ejecutores de todo tipo
Arauzo Almirón, Valentín
core +1 more source
ABSTRACT The rapid growth of the Internet of Things (IoT) creates concern around multilayer cyber‐attacks that exploit interactions between physical, network, and application layers. Traditional Intrusion Detection Systems (IDS) often utilize outdated datasets, high dimensional features, or computationally heavy deep learning models, which are not ...
Badeea Al Sukhni +4 more
wiley +1 more source
Graph‐Based Generative Adversarial Network for Adaptive IoT Intrusion Detection
The study introduces a hybrid graph‐based generative adversarial network (G‐GAN) that integrates adversarial learning with graph attention mechanisms to enhance intrusion detection in IoT environments. G‐GAN significantly improves accuracy and adaptability by reducing false alarms and detecting emerging threats in dynamic, heterogeneous IoT networks ...
Meshari H. Alanazi +7 more
wiley +1 more source
Visual analytics with decision tree on network traffic flow for botnet detection [PDF]
Visual analytics (VA) is an integral approach combining visualization, human factors, and data analysis. VA can synthesize information and derive insight from massive, dynamic, ambiguous and often conflicting data.
Ismail, Saiful Adli +5 more
core +1 more source
ABSTRACT Objective Recent growth of online research has been accompanied by an increase in reports of fraudulent participants, which can significantly comprise research validity. Drawing from our experience using Qualtrics with open recruitment, existing literature, and emerging studies in eating disorders (ED), we outline the risk and provide simple ...
Jamie‐Lee Pennesi +2 more
wiley +1 more source
Botnets are emerging as the most serious threat against cyber-security as they provide adistributed platform for several illegal activities such as launching distributed denial of service attacksagainst critical targets, malware dissemination, phishing ...
Harshita Kanani (576566) +1 more
core +1 more source

