Abstract
This article proposes a unified threat landscape for participatory crowd sensing (P-CS) systems. Specifically, it focuses on attacks from organized malicious actors that may use the knowledge of P-CS platform's operations and exploit algorithmic weaknesses in AI-based methods of event trust, user reputation, decision-making, or recommendation models deployed to preserve information integrity in P-CS. We emphasize on intent driven malicious behaviors by advanced adversaries and how attacks are crafted to achieve those attack impacts. Three directions of the threat model are introduced, such as attack goals, types, and strategies. We expand on how various strategies are linked with different attack types and goals, underscoring formal definition, their relevance, and impact on the P-CS platform.
Recommended Citation
S. Bhattacharjee and S. K. Das, "Unifying Threats Against Information Integrity In Participatory Crowd Sensing," IEEE Pervasive Computing, Institute of Electrical and Electronics Engineers; Computer Society, Jan 2023.
The definitive version is available at https://doi.org/10.1109/MPRV.2023.3296271
Department(s)
Computer Science
Keywords and Phrases
Decision making; Economics; Sensors; Servers; Social networking (online); Threat modeling; Urban areas
International Standard Serial Number (ISSN)
1558-2590; 1536-1268
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2023 Institute of Electrical and Electronics Engineers; Computer Society, All rights reserved.
Publication Date
01 Jan 2023
