Fraud detection refers to the set of measures and practices used to identify and prevent fraudulent activity, such as credit card fraud or identity theft.
Fraud detection in IoT refers to the set of measures and practices used to identify and prevent fraudulent activity within the connected network of devices and systems. This includes the use of specialized security controls and technologies to monitor data and device activity for signs of fraud, as well as policies and procedures to ensure the confidentiality, integrity, and availability of information. In the context of IoT security, fraud detection is critical to preventing cyber attacks and data breaches that can compromise the security of connected devices and the data they transmit. Examples of fraud detection technologies in IoT include anomaly detection, machine learning algorithms, and behavioral analytics, which can identify unusual patterns of activity that may indicate fraudulent behavior.