A Secure-Enhanced Data Aggregation Based on ECC in Wireless Sensor Networks

Zhou, Qiang; Yang, Geng; He, Long

doi:10.3390/s140406701

Cited by 32 publications

(19 citation statements)

References 24 publications

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“…This means that aggregators are required to store keys for decryption and, thus, a compromised aggregator can reveal transmitting messages or forge aggregated results. To decrease this impact, homomorphic encryption schemes have been applied to WSNs [12][13][14]. By homomorphic encryption schemes, end-to-end data confidentiality is provided.…”

Section: Related Workmentioning

confidence: 99%

Data aggregation with end-to-end confidentiality and integrity for large-scale wireless sensor networks

Cui

Shao

et al. 2017

Peer-to-Peer Netw. Appl.

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In wireless sensor networks, data aggregation allows in-network processing, which leads to reduced packet transmissions and reduced redundancy, and thus is helpful to prolong the overall lifetime of wireless sensor networks. In current studies, Elliptic Curve ElGamal homomorphic encryption algorithm has been widely used to protect end-to-end data confidentiality. However, these works suffer from the expensive mapping function during decryption. If the aggregated results are huge, the base station has no way to gain the original data due to the hardness of the elliptic curve discrete logarithm problem. Therefore, these schemes are unsuitable for the large-scale WSNs. In this paper, we propose a secure energy-saving data aggregation scheme designed for the large-scale WSNs. We employ Okamoto-Uchiyama homomorphic encryption algorithm to protect end-to-end data confidentiality, use MAC to achieve in-network false data filtering, and utilize the homomorphic MAC algorithm to achieve end-to-end data integrity. Two popular IEEE 802.15.4-compliant wireless sensor network platforms, Tmote Sky and iMote 2 have been used to evaluate the efficiency and feasibility of our scheme. The results demonstrate that our scheme achieved better performance in reducing energy consumption.Moreover, system delay, especially decryption delay at the base station, has been reduced when compared to other state-of-art methods.

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Section: Related Workmentioning

confidence: 99%

Data aggregation with end-to-end confidentiality and integrity for large-scale wireless sensor networks

Cui

Shao

et al. 2017

Peer-to-Peer Netw. Appl.

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“…There are also many secure aggregation methods, such as [23][24][25][26]. However, most of these works adapt the traditional multihop wireless sensor networks, and they are not suitable for TWSNs.…”

Section: Related Workmentioning

confidence: 99%

Random Secure Comparator Selection Based Privacy-Preserving MAX/MIN Query Processing in Two-Tiered Sensor Networks

et al. 2016

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Privacy-preserving data queries for wireless sensor networks (WSNs) have drawn much attention recently. This paper proposes a privacy-preserving MAX/MIN query processing approach based on random secure comparator selection in two-tiered sensor network, which is denoted by RSCS-PMQ. The secret comparison model is built on the basis of the secure comparator which is defined by 0-1 encoding and HMAC. And the minimal set of highest secure comparators generating algorithm MaxRSC is proposed, which is the key to realize RSCS-PMQ. In the data collection procedures, the sensor node randomly selects a generated secure comparator of the maximum data into ciphertext which is submitted to the nearby master node. In the query processing procedures, the master node utilizes the MaxRSC algorithm to determine the corresponding minimal set of candidate ciphertexts containing the query results and returns it to the base station. And the base station obtains the plaintext query result through decryption. The theoretical analysis and experimental result indicate that RSCS-PMQ can preserve the privacy of sensor data and query result from master nodes even if they are compromised, and it has a better performance on the network communication cost than the existing approaches.

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“…Lin et al [14] proposed a new concealed data aggregation scheme, which is robustness and efficiency. Zhou et al [15] proposed a Secure-Enhanced Data Aggregation, which can achieve the highest security on the aggregated result compared with other asymmetric schemes.…”

Section: Journal Of Electrical and Computer Engineeringmentioning

confidence: 99%

A Secure Privacy-Preserving Data Aggregation Model in Wearable Wireless Sensor Networks

Zhang

2015

Journal of Electrical and Computer Engineering

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With the rapid development and widespread use of wearable wireless sensors, data aggregation technique becomes one of the most important research areas. However, the sensitive data collected by sensor nodes may be leaked at the intermediate aggregator nodes. So, privacy preservation is becoming an increasingly important issue in security data aggregation. In this paper, we propose a security privacy-preserving data aggregation model, which adopts a mixed data aggregation structure. Data integrity is verified both at cluster head and at base station. Some nodes adopt slicing technology to avoid the leak of data at the cluster head in innercluster. Furthermore, a mechanism is given to locate the compromised nodes. The analysis shows that the model is robust to many attacks and has a lower communication overhead.

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A Secure-Enhanced Data Aggregation Based on ECC in Wireless Sensor Networks

Cited by 32 publications

References 24 publications

Data aggregation with end-to-end confidentiality and integrity for large-scale wireless sensor networks

Data aggregation with end-to-end confidentiality and integrity for large-scale wireless sensor networks

Random Secure Comparator Selection Based Privacy-Preserving MAX/MIN Query Processing in Two-Tiered Sensor Networks

A Secure Privacy-Preserving Data Aggregation Model in Wearable Wireless Sensor Networks

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