학술논문

Rumor Source Detection With Multiple Observations Under Adaptive Diffusions
Document Type
Periodical
Source
IEEE Transactions on Network Science and Engineering IEEE Trans. Netw. Sci. Eng. Network Science and Engineering, IEEE Transactions on. 8(1):2-12 Jan, 2021
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Components, Circuits, Devices and Systems
Signal Processing and Analysis
Protocols
Diffusion processes
Maximum likelihood estimation
Social network services
Maximum likelihood detection
Electronic mail
Adaptation models
Information diffusion
social networks
source detection
source obfuscation
Language
ISSN
2327-4697
2334-329X
Abstract
Recent work, motivated by anonymous messaging platforms, has introduced adaptive diffusion protocols which can obfuscate the source of a rumor: a “snapshot adversary” with access to the subgraph of “infected” nodes can do no better than randomly guessing the entity of the source node. What happens if the adversary has access to multiple independent snapshots? We study this question when the underlying graph is the infinite $d$-regular tree. We show that (1) a weak form of source obfuscation is still possible in the case of two independent snapshots, but (2) already with three observations there is a simple algorithm that finds the rumor source with constant probability, regardless of the adaptive diffusion protocol. We also characterize the tradeoff between local spreading and source obfuscation for adaptive diffusion protocols (under a single snapshot). These results raise questions about the robustness of anonymity guarantees when spreading information in social networks.