SIA: Secure information aggregation in sensor networks

By Haowen Chan, Adrian Perrig, Bartosz Przydatek, Dawn Song. ACM International Conference on Embedded Networked Sensor Systems, 2003

1,023 citations recorded by the source corpus.

In sensor networks, data aggregation is a vital primitive enabling efficient data queries. An on-site aggregator device collects data from sensor nodes and produces a condensed summary which is forwarded to the off-site querier, thus reducing the communication cost of the query. Since the aggregator is on-site, it is vulnerable to physical compromise attacks. A compromised aggregator may report false aggregation results. Hence, it is essential that techniques are available to allow the querier to verify the integrity of the result returned by the aggregator node. We propose a novel framework for secure information aggregation in sensor networks. By constructing efficient random sampling mechanisms and interactive proofs, we enable the querier to verify that the answer given by the aggregator is a good approximation of the true value, even when the aggregator and a fraction of the sensor nodes are corrupted. In particular, we present efficient protocols for secure computation of the median and average of the measurements, for the estimation of the network size, for finding the minimum and maximum sensor reading, and for random sampling and leader election. Our protocols require only sublinear communication between the aggregator and the user.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/bf1c8dfc2e4c9f7d70b3a841c44c540acb00d36a

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In Computer Networks and Communications

Citations in the corpus

Sensor network security: a survey (2009, methodology): “Bidirectional authentication schemes [127] Neighbors’ certificate schemes [128-132] Scheme defending against one compromised node [126] Statistical method [133, 134] Plaintext based scheme Cipher based scheme [135136]”
A survey of security issues in mobile ad hoc and sensor networks (2005, background): “In [116] the authors have proposed a security framework based on an aggregate-commit-prove approach to verify that the answer given by aggregators is a good approximation of the true value even if the aggregators and a fraction of the sensor nodes can be corrupted.”
IoT for Smart Cities: Machine Learning Approaches in Smart Healthcare - A Review (2021, background): “The network used for such low-power wide area communication is known as a LPWAN (low-power wide area network) [27].”
Medians and beyond: new aggregation techniques for sensor networks (2004, background): “Przydatek et. al. [ 21 ] have discussed secure ways to aggregate data, but with only one aggregating node.”
Challenges in Securing Vehicular Networks (2005, neutral): “for sensor networks [17].”
SecureDAV: a secure data aggregation and verification protocol for sensor networks (2004, background): “B. Pryzdatek et al. proposed a novel framework for secure information aggregation in sensor networks [1].”
A Survey on Wireless Sensor Network Security (2009, background): “A number of secure and efficient routing protocols [28, 50, 49, 69], secure data aggregation protocols [21, 30, 52, 77, 64, 83] etc.”
LEAP+: Efficient security mechanisms for large-scale distributed sensor networks (2006, background): “Some of the other related works on sensor network security include secure data aggregation [Hu and Evans 2003; Przydatek et al. 2003; Yang et al. 2006], preventing false data injection attacks [Ye et al. 2004; Zhu et al. 2004], detecting node replication attacks [Parno et al. 2005] and Sybil…”
Secure hierarchical in-network aggregation in sensor networks (2006, methodology): “[17] but extend their single aggregator model to a fully distributed setting.”
LEAP: efficient security mechanisms for large-scale distributed sensor networks (2003, background): “Some of the other related works on sensor network security include secure data aggregation [Hu and Evans 2003; Przydatek et al. 2003; Yang et al. 2006], preventing false data injection attacks [Ye et al. 2004; Zhu et al. 2004], detecting node replication attacks [Parno et al. 2005] and Sybil attac”
Countermeasures Against Traffic Analysis Attacks in Wireless Sensor Networks (2005, background): “secure data communication [17], secure routing [14, 12, 5], secure data aggregation [19], and pairwise key setup [8, 3, 7, 15, 26].”
Synopsis diffusion for robust aggregation in sensor networks (2004, methodology): “Count Distinct can be done using a trivial adaption of Flajolet and Martin s algorithm (FM) [8].”
An interleaved hop-by-hop authentication scheme for filtering of injected false data in sensor networks (2004, background): “Przydatek et al [16] present SIA, a secure information aggregation scheme for sensor networks.”
Efficient aggregation of encrypted data in wireless sensor networks (2005, methodology): “Although not related to data priv acy , in [ 14 ] Przydatek, et al. presen t ecien t mec hanism for detecting forged aggregation v alues (min, max, median, a v erage and coun t). In their setting, a trusted outside user can query the WSN.”