Resilient aggregation in sensor networks

By David A. Wagner. 2004

438 citations recorded by the source corpus.

Subfields: Computer Networks and Communications

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In Computer Networks and Communications

Citations in the corpus

Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer (2019, background): “Weighted average aggregation cannot tolerate even a single malicious party [13], [53].”
Reputation-based framework for high integrity sensor networks (2004, background): “As shown in [Wagner 2004], a single corrupted sensor can drastically change the aggregation metrics, such as average, maximum, minimum etc.”
Efficient aggregation of encrypted data in wireless sensor networks (2005, background): “Another work by Wagner [9] examines security of aggregation in WSNs, describing attacks against existing aggregation schemes before providing a framework in which to evaluate such a scheme’s security.”
SIA: Secure information aggregation in sensor networks (2003, background): “Wagner [36] studied what aggregation functio s may be more resilient against malicious attacks.”
PDA: Privacy-Preserving Data Aggregation in Wireless Sensor Networks (2007, background): “Work presented in [10], [11], [12] investigates secure data aggregation schemes in the face of adversaries who try to tamper with nodes or steal the information.”
Wireless Sensor Network Security: A Survey (2006, background): “Using this framework, they argue that the aggregation functionalities that can be securely and meaningfully computed, in the presence of k compromised nodes, are exactly the functions that are (k, α)resilient for some α is not too large [76].”
Securing wireless sensor networks: a survey (2008, methodology): “Wagner [152] proposed to use statistical estimation to model the data fusion procedure so that the well-established estimation theory can be used to evaluate the resilience of fusion function.”
Secure hierarchical in-network aggregation in sensor networks (2006, background): “Wagner [18] performed a quantitative study measuring the effect of direct data injection on various aggregates, and concludes that the aggregates addressed in this paper (truncated SUM and AVERAGE, COUNT and Φ-QUANTILE) can be resilient under such attacks.”
Sensor network security: a survey (2009, methodology): “Another approach in [134] also applies a robust statistics estimation model with noisy and error-prone data to the problem of securing aggregation in the presence of malicious or spoofed data.”
On Data-Centric Trust Establishment in Ephemeral Ad Hoc Networks (2008, methodology): “V-C, our approach can be used as a resilient data aggregation technique in the sense defined in [28], a feature that distinguishes it from the above metioned works.”
Security in Wireless Sensor Networks (2008, neutral): “Wagner (2004) analyzes the resiliency of aggregation techniques, and argues that current aggregation techniques were proposed without security in mind, and thus, are vulnerable to attacks.”
A Survey on Wireless Sensor Network Security (2009, background): “Wagner studied secure data aggregation in sensor networks and proposed a mathematical framework for formally evaluating their security [71].”
A Review of Indoor Localization Techniques and Wireless Technologies (2021, background): “To give robustness to the system, outliers measurements are excluded by taking the median value of the sum [183].”
A survey of security issues in wireless sensor networks (2006, methodology): “Wagner studied secure data aggregation in sensor networks and proposed a mathematical framework for formally evaluating their security [ 93 ].”
SDAP: a secure hop-by-Hop data aggregation protocol for sensor networks (2006, methodology): “Some aggregation functions are found inherently insecure, such as MIN/MAX, because the change to a single sensor reading can cause noticeable changes to the final result [9].”