TY - GEN
T1 - PG
T2 - 31st ACM SIGSAC Conference on Computer and Communications Security, CCS 2024
AU - Jin, Chenglu
AU - Yin, Chao
AU - van Dijk, Marten
AU - Duan, Sisi
AU - Massacci, Fabio
AU - Reiter, Michael K.
AU - Zhang, Haibin
N1 - Publisher Copyright:
© 2024 Copyright held by the owner/author(s).
PY - 2024/12/9
Y1 - 2024/12/9
N2 - We design and implement PG, a Byzantine fault-tolerant and privacy-preserving multi-sensor fusion system. PG is flexible and extensible, supporting a variety of fusion algorithms and application scenarios. On the theoretical side, PG develops and unifies techniques from dependable distributed systems and modern cryptography. PG can provably protect the privacy of individual sensor inputs and fusion results. In contrast to prior works, PG can provably defend against pollution attacks and guarantee output delivery, even in the presence of malicious sensors that may lie about their inputs, contribute ill-formed inputs, and provide no inputs at all to sway the final result, and in the presence of malicious servers serving as aggregators. On the practical side, we implement PG in the client-server-sensor setting. Moreover, we deploy PG in a cloud-based system with 261 sensors and a cyber-physical system with 19 resource-constrained sensors. In both settings, we show that PG is efficient and scalable in both failure-free and failure scenarios.
AB - We design and implement PG, a Byzantine fault-tolerant and privacy-preserving multi-sensor fusion system. PG is flexible and extensible, supporting a variety of fusion algorithms and application scenarios. On the theoretical side, PG develops and unifies techniques from dependable distributed systems and modern cryptography. PG can provably protect the privacy of individual sensor inputs and fusion results. In contrast to prior works, PG can provably defend against pollution attacks and guarantee output delivery, even in the presence of malicious sensors that may lie about their inputs, contribute ill-formed inputs, and provide no inputs at all to sway the final result, and in the presence of malicious servers serving as aggregators. On the practical side, we implement PG in the client-server-sensor setting. Moreover, we deploy PG in a cloud-based system with 261 sensors and a cyber-physical system with 19 resource-constrained sensors. In both settings, we show that PG is efficient and scalable in both failure-free and failure scenarios.
KW - Fault-Tolerant Algorithms
KW - Garbled Circuit
KW - Guaranteed Output Delivery
KW - Sensor Fusion
UR - https://www.scopus.com/pages/publications/85215534281
U2 - 10.1145/3658644.3670343
DO - 10.1145/3658644.3670343
M3 - Conference contribution
AN - SCOPUS:85215534281
T3 - CCS 2024 - Proceedings of the 2024 ACM SIGSAC Conference on Computer and Communications Security
SP - 3272
EP - 3286
BT - CCS 2024 - Proceedings of the 2024 ACM SIGSAC Conference on Computer and Communications Security
PB - Association for Computing Machinery, Inc
Y2 - 14 October 2024 through 18 October 2024
ER -