Privacy-preserving max/min query in two-tiered wireless sensor networks

Yao, Yonglei; Xiong, Naixue; Park, Jong Hyuk; Ma, Li; Liu, Jingfa

doi:10.1016/j.camwa.2012.02.003

Cited by 82 publications

(55 citation statements)

References 22 publications

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“…We adopt the prefix membership verification scheme [27]- [30] as the building block of our MHDA ⊕ . The prefix membership verification scheme's basic idea is to transform the question of verifying whether a datum belongs to a range into a few issues of verifying whether two numerical value are equal.…”

Section: A Basic Ideamentioning

confidence: 99%

PPM-HDA: Privacy-Preserving and Multifunctional Health Data Aggregation With Fault Tolerance

Han

Zhao

et al. 2016

IEEE Trans.Inform.Forensic Secur.

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Wireless Body Area Networks (WBANs), as a promising health-care system, can provide tremendous benefits for timely and continuous patient care and remote health monitoring. Owing to the restriction of communication, computation and power in WBANs, cloud assisted WBANs, which offer more reliable, intelligent, and timely health-care services for mobile users and patients, are receiving increasing attention. However, how to aggregate the health data multifunctionally and efficiently is still an open issue to the cloud server (CS). In this paper, we propose a privacy-preserving and multifunctional health data aggregation mechanism (PPM-HDA) with fault tolerance for cloud assisted WBANs. With PPM-HDA, the CS can compute multiple statistical functions of users' health data in a privacy-preserving way to offer various services. Specifically, we first propose a multifunctional health data additive aggregation scheme (MHDA + ) to support additive aggregate functions such as average and variance. Then we put forward MHDA ⊕ as an extension of MHDA + to support non-additive aggregations such as min/max, median, percentile and histogram. PPM-HDA can resist differential attacks, which most existing data aggregation schemes suffer from. The security analysis shows that PPM-HDA can protect users' privacy against many threats. Performance evaluations illustrate that the computational overhead of MHDA + is significantly reduced with the assistance of CSs. Our MHDA ⊕ scheme is more efficient than previously reported min/max aggregation schemes in terms of communication overhead when the applications require large plaintext space and highly-accurate data.

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Section: A Basic Ideamentioning

confidence: 99%

PPM-HDA: Privacy-Preserving and Multifunctional Health Data Aggregation With Fault Tolerance

Han

Zhao

et al. 2016

IEEE Trans.Inform.Forensic Secur.

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“…Recently, the secure range query [5][6][7][8][9][10][11] and top-k query [12][13][14][15][16][17] have been broadly studied. However, there are limited researches on MAX/MIN query, and only [18,19] propose solutions of privacy-preserving MAX/MIN query in TWSN.…”

Section: Related Workmentioning

confidence: 99%

“…For MAX/MIN query, the same PMV as in [9,10], the symmetric encryption and HMAC are used in [18] to achieve the privacy-preserving MAX/MIN query processing. Since more codes are transmitted in data submission, which are generated by using the PMV and HMAC functions, the energy consumption of [18] is high, which will reduce the lifetime of whole network. In contrast, our former work [19] adapts 0-1 encoding verification instead of PMV to achieve an energy-efficient privacy-preserving MAX/MIN query which is denoted by EMQP.…”

Section: Related Workmentioning

confidence: 99%

“…In contrast, our former work [19] adapts 0-1 encoding verification instead of PMV to achieve an energy-efficient privacy-preserving MAX/MIN query which is denoted by EMQP. In EMQP, the codes generated by using 0-1 encoding and HMAC of same data are significantly less than those generated in [18], which can reduce the energy consumption of sensor nodes. Furthermore, in this paper, we will adopt random selection of codes on the basis of EMQP to save much more energy and accomplish better privacypreserving MAX/MIN query processing.…”

Section: Related Workmentioning

confidence: 99%

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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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“…On the one hand, sensor nodes can save much energy and avoid communication bottleneck by sending data to their closest storage nodes instead of the sink [2], meanwhile, it can also reduce storage cost. On the other hand, the query processing becomes more efficient since the sink only needs to communicate with several storage nodes rather than a large amount of sensor nodes [3]. Therefore, the tiered architecture is favorable for extending capacity and improving scalability of WSNs.…”

Section: Introductionmentioning

confidence: 99%

A Secure Collusion-Aware and Probability-Aware Range Query Processing in Tiered Sensor Networks

Dong¹,

Chen

Zhu

et al. 2015

2015 IEEE 34th Symposium on Reliable Distributed Systems (SRDS)

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Abstract-With high expansibility and efficient power usage, tiered wireless sensor networks are widely deployed in many fields as an important part of Internet of Things (IoTs). It is challenging to process range query while protecting sensitive data from adversaries. Moreover, most existing work focuses on privacy-preserving range query neglecting collusion attacks and probability attacks, which are more threatening to network security. In this paper, we first propose a secure range query protocol called secRQ, which not only protects data privacy, but also resists collusion attacks and probability attacks in tiered wireless sensor networks. Generalized inverse matrices and distance-based range query mechanism are used to guarantee security as well as high efficiency and accuracy. Besides, we propose the mutual verification scheme to verify the integrity of query results. Finally, both theoretical analysis and experimental results confirm the security, efficiency and accuracy of secRQ.

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Privacy-preserving max/min query in two-tiered wireless sensor networks

Cited by 82 publications

References 22 publications

PPM-HDA: Privacy-Preserving and Multifunctional Health Data Aggregation With Fault Tolerance

PPM-HDA: Privacy-Preserving and Multifunctional Health Data Aggregation With Fault Tolerance

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

A Secure Collusion-Aware and Probability-Aware Range Query Processing in Tiered Sensor Networks

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