Identifying personal physiological data risks to the Internet of Everything: the case of facial data breach risks

This study uses fault tree analysis to identify risks associated with facial data breaches in the Internet of Everything (IoE) environment. The analysis reveals three intermediate events contributing to breaches: personal factors, data management issues, and a lack of supervision. Two major basic events are identified as root causes: inadequate laws and regulations, and the immaturity of facial recognition technology. The findings highlight the need for robust policies and regulations to ensure data security and for increased individual awareness of data management practices.

Meng Wang, Yalin Qin, Jiaojiao Liu, Weidong Li