.png){kind=icon}
Return
Detecting inference attacks involving sensor data
.png){kind=icon}
PRE
AI
DOI：10.1016/j.iot.2026.102021.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Sharing and processing personal information with organizations has become increasingly essential for social interaction. In Europe, under the GDPR (General Data Protection Regulation), they must protect the data they collect by design and by default. Access Control (AC) mechanisms have traditionally been used to secure information systems against unauthorized access to sensitive data. However, the increasing availability of sensor data is motivating new services to provide information about individuals. Various data mining algorithms have been proposed to infer new personal data from sensor data. Sensitive data can be accessed indirectly using non-sensitive data, such as information inferred from sensor data. Therefore, there is a risk of bypassing AC mechanisms to obtain information using sensor data.
Journal
IF:
7.6
Papers:
2.0K
Citations:
6.9K
Organization
Cited Papers
.png){kind=icon}
ShareSave
ShareSaveShareSave
View more