Adequate defenses against sensor environment manipulation in decentralized sensor networks

Develop adequate methods to address sensor environment threats in decentralized sensor networks, including DePINs and participatory sensing networks, where adversaries can alter the physical environment or sensor placement to induce misleading readings that appear valuable to the network.

Background

The paper identifies a distinct class of attacks where participants manipulate the physical environment or placement of sensors to generate deceptive but seemingly valuable data. Unlike device or network threats, these attacks target the physical context of measurement.

The authors explicitly state that there is not yet an adequate way to address this class of threats, indicating the need for novel detection, validation, or incentive-compatible mechanisms that can robustly mitigate environment manipulation without unduly restricting network growth or openness.