Secure and highly-available aggregation queries in large-scale sensor networks via set sampling
Wireless sensor networks are often queried for aggregates such as predicate count, sum, and average. In untrusted environments, sensors may potentially be compromised. Existing approaches for securely answering aggregation queries in untrusted sensor networks can detect whether the aggregation resul...
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| Published in: | 2009 International Conference on Information Processing in Sensor Networks pp. 1 - 12 |
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| Main Author: | |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
Washington, DC, USA
IEEE Computer Society
13.04.2009
IEEE |
| Series: | ACM Conferences |
| Subjects: |
Information systems
> Data management systems
> Database management system engines
> Database query processing
Information systems
> Data management systems
> Database management system engines
> Parallel and distributed DBMSs
Mathematics of computing
> Probability and statistics
> Statistical paradigms
> Statistical graphics
Theory of computation
> Theory and algorithms for application domains
> Database theory
> Database query processing and optimization (theory)
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| ISBN: | 1424451086, 9781424451081 |
| Online Access: | Get full text |
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| Abstract | Wireless sensor networks are often queried for aggregates such as predicate count, sum, and average. In untrusted environments, sensors may potentially be compromised. Existing approaches for securely answering aggregation queries in untrusted sensor networks can detect whether the aggregation result is corrupted by an attacker. However, the attacker (controlling the compromised sensors) can keep corrupting the result, rendering the system unavailable. This paper aims to enable aggregation queries to tolerate instead of just detecting the adversary. To this end, we propose a novel tree sampling algorithm that directly uses sampling to answer aggregation queries. It leverages a novel set sampling technique to overcome a key and well-known obstacle in sampling — traditional sampling technique is only effective when the predicate count or sum is large. Set sampling can efficiently sample a set of sensors together, and determine whether any sensor in the set satisfies the predicate (but not how many). With set sampling as a building block, tree sampling can provably generate a correct answer despite adversarial interference, while without the drawbacks of traditional sampling techniques. |
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| AbstractList | Wireless sensor networks are often queried for aggregates such as predicate count, sum, and average. In untrusted environments, sensors may potentially be compromised. Existing approaches for securely answering aggregation queries in untrusted sensor networks can detect whether the aggregation result is corrupted by an attacker. However, the attacker (controlling the compromised sensors) can keep corrupting the result, rendering the system unavailable. This paper aims to enable aggregation queries to tolerate instead of just detecting the adversary. To this end, we propose a novel tree sampling algorithm that directly uses sampling to answer aggregation queries. It leverages a novel set sampling technique to overcome a key and well-known obstacle in sampling - traditional sampling technique is only effective when the predicate count or sum is large. Set sampling can efficiently sample a set of sensors together, and determine whether any sensor in the set satisfies the predicate (but not how many). With set sampling as a building block, tree sampling can provably generate a correct answer despite adversarial interference, while without the drawbacks of traditional sampling techniques. |
| Author | Haifeng Yu |
| Author_xml | – sequence: 1 surname: Haifeng Yu fullname: Haifeng Yu organization: National University of Singapore, Singapore |
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| PublicationTitle | 2009 International Conference on Information Processing in Sensor Networks |
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| Snippet | Wireless sensor networks are often queried for aggregates such as predicate count, sum, and average. In untrusted environments, sensors may potentially be... |
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| SubjectTerms | Aggregates Base stations Computer security Computer systems organization -- Architectures -- Distributed architectures Information systems -- Data management systems -- Database management system engines -- Database query processing Information systems -- Data management systems -- Database management system engines -- Parallel and distributed DBMSs Interference Large-scale systems Mathematics of computing -- Probability and statistics -- Statistical paradigms Mathematics of computing -- Probability and statistics -- Statistical paradigms -- Statistical graphics Networks -- Network types -- Mobile networks Networks -- Network types -- Wireless access networks Protocols Sampling methods Security and privacy -- Database and storage security Sensor phenomena and characterization Sensor systems Theory of computation -- Theory and algorithms for application domains -- Database theory -- Database query processing and optimization (theory) Theory of computation -- Theory and algorithms for application domains -- Database theory -- Theory of database privacy and security Wireless sensor networks |
| Title | Secure and highly-available aggregation queries in large-scale sensor networks via set sampling |
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