Data aggregator

About: Data aggregator is a research topic. Over the lifetime, 2615 publications have been published within this topic receiving 40265 citations.

Secure data aggregation without persistent cryptographic operations in wireless sensor networks

Abstract: In-network data aggregation in an essential operation to reduce energy consumption in large-scale wireless sensor networks With data aggregation, however, raw data items are invisible to the base station and thus the authenticity of the aggregated data is hard to guarantee A compromised sensor node may forge an aggregation value and mislead the base station into trusting a false reading Due to the stringent constraints of energy supply and computing capability on sensor nodes, it is challenging to detect a compromised sensor node and keep it from cheating This paper proposes a secure aggregation tree (SAT) to detect and prevent cheating Our method is essentially different from other existing solutions in that it does not require any cryptographic operations when all sensor nodes work honestly The detection of cheating is based on the topological constraints in the aggregation tree

Redirecting traffic via tunnels to discovered data aggregators

Abstract: In one embodiment, a data aggregator discovery (DAD) message may be distributed by an associated data aggregator, the DAD message identifying the initiating data aggregator, and comprising a recorded route taken from the data aggregator to a receiving particular node as well as a total path cost for the particular node to reach a root node of the DAG through the recorded route and via the data aggregator The receiving particular node determines a path cost increase (PCI) associated with use of the data aggregator based on the total path cost as compared to a DAG-based path cost for the particular node to reach the root node via the DAG If the PCI is below a configured threshold, the particular node may redirect traffic to the data aggregator as source-routed traffic according to the recorded route The traffic may then be aggregated by the data aggregator, accordingly

Distributed Data Privacy Preservation in IoT Applications

Abstract: Recently, the Internet of Things (IoT) has penetrated many aspects of the physical world to realize different applications. Through IoT, these applications generate, exchange, aggregate, and analyze a vast amount of security-critical and privacy- sensitive data, which makes them attractive targets of attacks. Therefore, it is rather necessary for IoT systems to be equipped with the ability to resist security and privacy risks when fulfilling the desired functional requirements and services. To achieve these goals, there are many new challenges for IoT to implement privacy preserving data manipulation. First, data analysts need to process privacy-sensitive data to extract the expected information without privacy disclosure. In addition, many privacy related factors, including privacy valuation and risk assessment, affect sensitive and private data trading between data owners and requesters. Moreover, the data owners' security behavior also plays an important role in privacy protection in IoT applications. Concerning these issues, this article introduces and surveys privacy preserving techniques in the processes of data aggregation, trading, and analysis: the balance between data analysis and privacy preservation from the data analysts' perspective, secure data trading from the perspective of data owners and requesters, and secure private data aggregation from the data owners' perspective.

Efficient Privacy-Preserving Multi-Dimensional Data Aggregation Scheme in Smart Grid

Abstract: Smart grid, characterized by high efficiency, security, and flexibility, is gradually replacing the traditional power grid. Data aggregation technology is frequently used to avoid user privacy disclosure as a result of power consumption data transmission in the smart grid. However, traditional one-dimensional data aggregation schemes fail to meet the demands of fine-grained analysis. Therefore, this paper proposes an efficient privacy-preserving multi-dimensional data aggregation (P 2 MDA) scheme in smart grid by virtue of homomorphic encryption and superincreasing sequence. The security analysis indicates that the proposed scheme is proved to be secure in the random oracle model, satisfying all security and privacy requirements. The extensive performance analysis shows that in comparison to the related schemes, the proposed scheme achieves lowest computation and communication costs, thus appropriate for practical applications.

CSDA: a novel cluster-based secure data aggregation scheme for WSNs

Abstract: With the development of wireless sensor networks, privacy-preserving has become a very important problem in numerous wireless sensor networks (WSN) applications. This paper presents a novel energy-efficient secure data aggregation scheme cluster-based private data aggregation (CSDA) based on cluster privacy-preserving. It has good flexibility and practical applicability using the slice-assemble technology. And, the number of fragments will dynamically change from the change of the network scale. Then, it can reduce communication overhead and energy consumption. Finally, the simulation results show that the proposed aggregation method demonstrates better performance in data aggregation precision, privacy-preserving and communication efficiency than other methods.