In our CyberWIKI we want to present and explain the most important terms and definitions in the context of PHYSICS.
Machine Learning (ML) is a subfield of AI that focuses on the development of algorithms and statistical models that allow computers to learn from data and make predictions or decisions. Rather than explicitly programming a machine to do specific tasks, ML algorithms allow machines to recognize patterns and relationships in data and make predictions or take action without being explicitly programmed. ML algorithms can be classified into supervised learning, unsupervised learning, and reinforcement learning categories based on the nature of the data and the learning process.
In summary, AI is a broader concept aimed at developing intelligent machines, while machine learning is a specific approach within AI that focuses on algorithms and models that enable machines to learn from data and make predictions or decisions.
• Radio Jamming: Using a jammer to block or disrupt wireless communications by reducing the signal-to-noise ratio.
• Radio Sniffing: Eavesdropping on the signal and intercepting information at the PHY level.
• RF Spoofing: Sending out a fake signal masquerading as a real signal. This could also be used for a man-in-the-middle or relay attack.
– Vehicle platooning: These are dynamically formed vehicle platoons in which a leading vehicle transmits information to the vehicles that are part of the platoon.
– Advanced Driving: Both vehicles and Roadside Units (RSUs) can share data collected by sensors with vehicles in their vicinity. This allows the vehicles to dynamically coordinate their trajectories.
– Advanced sensors: Exchange of sensor data or video information between vehicles, pedestrians, infrastructure, etc.
– Remote Control: Remote control of a vehicle either by a human operator or a V2X server.
The exact implementation of Colour Shift Modulation may vary depending on the specific application or context. It could involve techniques such as color space conversions, lookup tables, color correction algorithms, or other image processing methods.
Resiliency is the ability of the network or system to provide and maintain an acceptable level of service despite various failures and challenges to normal operations. Cyber resilience is the ability to prepare for, respond to, and recover from cyber attacks while continuing to operate effectively. The cyber resilience life cycle starts with monitoring the network, continues with the prevention and detection of attacks and adapts different strategies.