research-article

Congestion lower bounds for secure in-network aggregation

Authors:

Raghav Bhaskar,

Ragesh Jaiswal,

Sidharth TelangAuthors Info & Claims

WISEC '12: Proceedings of the fifth ACM conference on Security and Privacy in Wireless and Mobile Networks

Pages 197 - 204

https://doi.org/10.1145/2185448.2185474

Published: 16 April 2012 Publication History

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Abstract

In-network aggregation is a technique employed in Wireless Sensor Networks (WSNs) to aggregate information flowing from the sensor nodes towards the base station. It helps in reducing the communication overhead on the nodes in the network and thereby increasing the longevity of the network. We study the problem of maintaing integrity of the aggregate value, when the aggregate function is SUM, in the presence of compromised sensor nodes. We focus on one-round, end-to end, secure aggregation protocols and give a strong, formal security defintion. We show that a worst-case lower bound of Ω(n) applies on the congestion (maximum size of message between any two nodes) in such protocols, where n is the number of nodes in the network. This is the first such result showing that the most basic protocols are the best one-round in-network aggregation protocols with respect to congestion. We also show that against a weaker adversary (which does not compromise nodes), we can achieve secure in-network aggregation protocols with a congestion of O(log₂n).

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Zhang QZhao GXu HYang P(2024)XAgg: Accelerating Heterogeneous Distributed Training Through XDP-Based Gradient AggregationIEEE/ACM Transactions on Networking10.1109/TNET.2023.333952432:3(2174-2188)Online publication date: Jun-2024
https://doi.org/10.1109/TNET.2023.3339524
Fang JZhao GXu HWu CYu Z(2023)GRID: Gradient Routing With In-Network Aggregation for Distributed TrainingIEEE/ACM Transactions on Networking10.1109/TNET.2023.324479431:5(2267-2280)Online publication date: Oct-2023
https://doi.org/10.1109/TNET.2023.3244794
Wang HQin YLao CLe YWu WChen K(2023)Preemptive Switch Memory Usage to Accelerate Training Jobs with Shared In-Network Aggregation2023 IEEE 31st International Conference on Network Protocols (ICNP)10.1109/ICNP59255.2023.10355574(1-12)Online publication date: 10-Oct-2023
https://doi.org/10.1109/ICNP59255.2023.10355574

Index Terms

Congestion lower bounds for secure in-network aggregation
1. Security and privacy
  1. Network security

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Published In

WISEC '12: Proceedings of the fifth ACM conference on Security and Privacy in Wireless and Mobile Networks

April 2012

216 pages

ISBN:9781450312653

DOI:10.1145/2185448

General Chairs:
Marwan Krunz
University of Arizona, USA
,
Loukas Lazos
University of Arizona, USA
,
Program Chairs:
Roberto Di Pietro
Università di Roma Tre, Italy
,
Wade Trappe
Rutgers University, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

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Association for Computing Machinery

New York, NY, United States

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Published: 16 April 2012

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WISEC'12: Fifth ACM Conference on Security and Privacy in Wireless and Mobile Networks

April 16 - 18, 2012

Arizona, Tucson, USA

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Zhang QZhao GXu HYang P(2024)XAgg: Accelerating Heterogeneous Distributed Training Through XDP-Based Gradient AggregationIEEE/ACM Transactions on Networking10.1109/TNET.2023.333952432:3(2174-2188)Online publication date: Jun-2024
https://doi.org/10.1109/TNET.2023.3339524
Fang JZhao GXu HWu CYu Z(2023)GRID: Gradient Routing With In-Network Aggregation for Distributed TrainingIEEE/ACM Transactions on Networking10.1109/TNET.2023.324479431:5(2267-2280)Online publication date: Oct-2023
https://doi.org/10.1109/TNET.2023.3244794
Wang HQin YLao CLe YWu WChen K(2023)Preemptive Switch Memory Usage to Accelerate Training Jobs with Shared In-Network Aggregation2023 IEEE 31st International Conference on Network Protocols (ICNP)10.1109/ICNP59255.2023.10355574(1-12)Online publication date: 10-Oct-2023
https://doi.org/10.1109/ICNP59255.2023.10355574

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In-network aggregation trade-offs for data collection in wireless sensor networks

Q-learning based routing for in-network aggregation in wireless sensor networks

SAPC: A Secure Aggregation Protocol for Cluster-Based Wireless Sensor Networks

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