Abstract: This research pioneers an NS2 (Network Simulator 2)-driven Network Intrusion Detection System (NIDS) for smart city cybersecurity, leveraging NS2's discrete-event simulation to model ...

Restoration Experts Share Critical Warning Signs Property Owners Often Overlook Until Costly Damage Occurs TAMPA, FL, ...

By Ben TAGOE In the modern cybersecurity landscape, computer networking serves as both the foundation of organizational ...

Synthetic data allows regulators to test the resilience of critical infrastructure defenders under extreme hypothetical scenarios.

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

This project implements an Intrusion Detection System using machine learning algorithms to detect malicious network activities. It analyzes network traffic patterns, packet headers, and flow data to ...

The accelerating sophistication of cyberattacks poses unprecedented challenges for national security, critical infrastructures, and global digital resilience. Traditional signature-based defenses have ...

Abstract: Traditional intrusion detection systems (IDSs), leveraging machine learning (ML) algorithms, have improved the detection accuracy of unknown attacks by continuously updating ML models but ...

An overview of attention detection using EEG signals, which includes six steps: an experimental paradigm design, in which the task and the stimuli are defined and presented to the subjects; EEG data ...