一种可检测数据完整性的隐私数据融合算法

针对无线传感器网络数据融合中可能出现的数据篡改和隐私泄露等问题,该文提出一种可进行完整性检测的无线传感器网络隐私数据融合算法 ICKPDA.该算法首先在感知数据中嵌入私密种子,对真实数据进行隐藏;然后通过数据分片和聚集技术,增强数据的隐私保护性;最后利用数据间的关联特性在基站进行完整性检测.仿真结果显示,相比于其它算法,ICKPDA 在保证融合结果精确的前提下,能有效地进行数据完整性检测和隐私保护,同时花费较少的数据通信量和计算量.     

传感器网络数据融合隐私保护及安全框架

在传感器网络中,隐私保护和入侵检测是一对矛盾关系,调和两者的矛盾非常重要。在传感器网络中传感数据融合是一个基本操作,研究隐私保护和入侵检测在传感数据融合中的关系并提出一个框架,可以探测错误数据融合,但不需要知道实际的传感数据内容,因而得以保证传感数据的隐蔽性。实验结果显示,实际的原始数据和聚合传感数据可以得到很好隐蔽的同时能够检测到大部分错误数据融合。     

一种支持完整性验证的隐私保护直方图融合算法

针对无线传感器网络隐私保护数据融合和完整性验证难以同时兼顾问题,提出一种支持完整性验证的隐私保护直方图融合算法（iPPHA ）。构建两棵融合树,分别传输融合数据和冗余信息,在基站处对融合结果的完整性进行验证。针对数据包丢失问题,设计了一种ID传输方案来提高可靠性。仿真结果显示,算法可以在不明显增加网络资源消耗的前提下,进行完整性验证。改进型ID传输方案可节约70％的通信开销。     

无线传感器网络中有效的安全数据融合机制

在无线传感器网络中,数据融合是实现有效传输和节省能源的一个重要途径,许多应用都需要可靠并且可信的数据来进行融合.针对上述要求,提出了一个新的安全数据融合算法来保证融合数据的机密性和完整性.算法使用端到端加密和逐跳加密相结合的方式进行数据传输,通过认证过程进行恶意节点及伪造数据的检测.仿真表明,提出的算法能够有效地检测出恶意节点,并保证融合结果的准确性.     

无线传感器网络数据隐私保护技术分析

随着无线传感器技术水平的提升,其所具备的应用范围不断的提升,发挥了十分重要的作用.对于网络数据安全来说,无线传感器网络数据隐私保护意义重大,由于比较容易出现窃取网络数据隐私的安全问题,需要采取相应的技术来保护网络数据隐私安全.在本文中,首先分析了无线传感器网络数据隐私面临的主要威胁,接着,在数据聚集、数据查询和访问控制三个方面分析了数据隐私保护技术,以便于提升保护的效果,保证网络数据安全.     

WSN中源节点隐私保护协议研究

无线传感器网络被广泛应(wireless sensor network,WSN)用于军事战场、环境监测等外部环境比较恶劣领域。又因为无线传感器网络依赖于无线通信,WSN节点资源受限,所以WSN安全问题相当突出。本文关注的是WSN中位置隐私保护问题,其中对源位置隐私保护进行了重点研究。文章首先对WSN的隐私保护问题进行了简单分类介绍,接着总结介绍了几种典型的源节点隐私保护方案,最后对评价源节点位置隐私保护协议有效性的协议度量标准进行了归纳总结。     

基于移动代理的WSN数据融合的研究

移动代理已广泛用于无线传感器网络并进行数据融合。该文将移动代理用于簇成员节点间进行数据收集并进行数据融合,并提出了基于精度的量化编码的数据融合算法。该算法有效减少了冗余数据,提高了传输速率,延长了无线传感器网络的寿命,并将其应用到森林防火中去。     

一种基于数据融合的WSN节点部署策略

采用非均匀的方法部署节点,提出了一种基于数据融合的节点部署策略.针对节点数据采集率恒定的圆形网络场景,根据避免能量空洞以及降低数据冗余度的思想部署传感器节点,通过该策略使得网络达到次级能耗均衡.仿真结果表明该方法能够缓解能量空洞问题,延长网络生命周期.     

无线传感器网络数据融合安全机制研究

由于WSNs本身资源方面存在的局限性和脆弱性,使其安全问题成为一大挑战。随着WSNs向大范围配置的方向发展,其安全问题越来越重要。围绕WSNs的安全需求,结合WSNs的分层网络结构,研究了其各层易遭受的攻击及防御对策。本文分析了基于明文的数据融合安全机制和基于密文的数据融合安全机制,并在此基础上提出了相应的解决思路。     

一种误差可控传输均衡的WSN数据融合算法

如何有效降低WSN(Wiretess Sensor Net work)网内数据传输量,延长WSN的寿命,是WSN领域的研究热点.在分簇WSN基础上,实现了一种误差实时可控的数据融合算法.通过该算法,节点可自行根据近期采集的历史数据实时调整传输阈值,不同节点可保持接近的数据传输率,实现均匀耗电;自适应的阈值可以有效控制数据融合的误差.理论分析与仿真实验表明,该算法能够保证不同节点数据传输的公平性;在数据传输率相同的情况下,其求和查询及均值查询的平均绝对误差均远低于当前优秀的基于伯努利采样的数据融合方法.此算法无需先验知识,在多种WSN应用场景中具有较强的可用性与适应性.     

State-of-the-art survey of privacy-preserving data aggregation in wireless sensor networks

A state-of-the-art survey of privacy-preserving data aggregation techniques in wireless sensor networks was reviewed.Firstly,preliminaries were introduced,including network models,adversary models,and performance evaluation metrics.Secondly,existing related work was classified into several types according to privacy preservation techniques,such as homomorphic encryption,data perturbation,slicing-mixing technique,generalization,secure multiparty computation,and the key mechanisms of typical protocols were elaborated and analyzed.Finally,the promising future research directions were discussed.     

A secure channel code‐based scheme for privacy preserving data aggregation in wireless sensor networks

Data aggregation is an efficient method to reduce the energy consumption in wireless sensor networks (WSNs). However, data aggregation schemes pose challenges in ensuring data privacy in WSN because traditional encryption schemes cannot support data aggregation. Homomorphic encryption schemes are promising techniques to provide end to end data privacy in WSN. Data reliability is another main issue in WSN due to the errors introduced by communication channels. In this paper, a symmetric additive homomorphic encryption scheme based on Rao‐Nam scheme is proposed to provide data confidentiality during aggregation in WSN. This scheme also possess the capability to correct errors present in the aggregated data. The required security levels can be achieved in the proposed scheme through channel decoding problem by embedding security in encoding matrix and error vector. The error vectors are carefully designed so that the randomness properties are preserved while homomorphically combining the data from different sensor nodes. Extensive cryptanalysis shows that the proposed scheme is secure against all attacks reported against private‐key encryption schemes based on error correcting codes. The performance of the encryption scheme is compared with the related schemes, and the results show that the proposed encryption scheme outperforms the existing schemes.     

High energy‐efficient and privacy‐preserving secure data aggregation for wireless sensor networks

An efficient data process technology is needed for wireless sensor networks composed of many sensors with constrained communication, computational, and memory resources. Data aggregation is presented as an efficient and significant method to reduce transmitted data and prolong lifetime for wireless sensor networks. Meanwhile, many applications require preserving privacy for secure data aggregation. In this paper, we propose a high energy‐efficient and privacy‐preserving scheme for secure data aggregation. Because of the importance of communication overhead and accuracy, our scheme achieves less communication overhead and higher data accuracy besides providing for privacy preservation. For extensive simulations, we evaluate and conclude the performance of our high energy‐efficient and privacy‐preserving scheme. The conclusion shows that the high energy‐efficient and privacy‐preserving scheme provides better privacy preservation and is more efficient than existing schemes. Copyright © 2012 John Wiley & Sons, Ltd.     

MDPA: multidimensional privacy‐preserving aggregation scheme for wireless sensor networks

In this paper, we propose a novel multidimensional privacy‐preserving data aggregation scheme for improving security and saving energy consumption in wireless sensor networks (WSNs). The proposed scheme integrates the super‐increasing sequence and perturbation techniques into compressed data aggregation, and has the ability to combine more than one aggregated data into one. Compared with the traditional data aggregation schemes, the proposed scheme not only enhances the privacy preservation in data aggregation, but also is more efficient in terms of energy costs due to its unique multidimensional aggregation. Extensive analyses and experiments are given to demonstrate its energy efficiency and practicability. Copyright © 2009 John Wiley & Sons, Ltd.     

Pareto-optimal clustering scheme using data aggregation for wireless sensor networks

The presence of cluster heads (CHs) in a clustered wireless sensor network (WSN) leads to improved data aggregation and enhanced network lifetime. Thus, the selection of appropriate CHs in WSNs is a challenging task, which needs to be addressed. A multicriterion decision-making approach for the selection of CHs is presented using Pareto-optimal theory and technique for order preference by similarity to ideal solution (TOPSIS) methods. CHs are selected using three criteria including energy, cluster density and distance from the sink. The overall network lifetime in this method with 50% data aggregation after simulations is 81% higher than that of distributed hierarchical agglomerative clustering in similar environment and with same set of parameters. Optimum number of clusters is estimated using TOPSIS technique and found to be 9–11 for effective energy usage in WSNs.     

基于数据融合的无线传感器网络路由算法

在分簇协议LEACH和链状协议PEGASIS的基础上,提出一种新的基于数据融合的分簇路由算法.簇首节点采用多跳方式传输数据,并根据周围节点的密集程度构造不同大小的簇;簇内节点计算上行和下行节点构造数据融合树,采用时分复用调度算法进行多跳路由.NS2仿真结果表明该路由算法均衡了各个节点的能量消耗,延长了网络存活时间,并降低了网络延迟.     

Secure data aggregation in wireless sensor networks using homomorphic encryption

In a Wireless Sensor Network (WSN), aggregation exploits the correlation between spatially and temporally proximate sensor data to reduce the total data volume to be transmitted to the sink. Mobile agents (MAs) fit into this paradigm, and data can be aggregated and collected by an MA from different sensor nodes using context specific codes. The MA-based data collection suffers due to large size of a typical WSN and is prone to security problems. In this article, homomorphic encryption in a clustered WSN has been proposed for secure and efficient data collection using MAs. The nodes keep encrypted data that are given to an MA for data aggregation tasks. The MA performs all the data aggregation operations upon encrypted data as it migrates between nodes in a tree-like structure in which the nodes are leafs and the cluster head is the root of the tree. It returns and deposits the encrypted aggregated data to the cluster head after traversing through all the intra cluster nodes over a shortest path route. The homomorphic encryption and aggregation processing in encrypted domain makes the data collection process secure. Simulation results confirm the effectiveness of the proposed secure data aggregation mechanism. In addition to security, MA-based mechanism leads to lesser delay and bandwidth requirements.     

PRDA: polynomial regression‐based privacy‐preserving data aggregation for wireless sensor networks

In wireless sensor networks, data aggregation protocols are used to prolong the network lifetime. However, the problem of how to perform data aggregation while preserving data privacy is challenging. This paper presents a polynomial regression‐based data aggregation protocol that preserves the privacy of sensor data. In the proposed protocol, sensor nodes represent their data as polynomial functions to reduce the amount of data transmission. In order to protect data privacy, sensor nodes secretly send coefficients of the polynomial functions to data aggregators instead of their original data. Data aggregation is performed on the basis of the concealed polynomial coefficients, and the base station is able to extract a good approximation of the network data from the aggregation result. The security analysis and simulation results show that the proposed scheme is able to reduce the amount of data transmission in the network while preserving data privacy. Copyright © 2013 John Wiley & Sons, Ltd.     

A faulty node detection scheme for wireless sensor networks that use data aggregation for transport

This paper presents a faulty node detection approach for wireless sensor networks that aggregate measurement data on their way toward the sink (base station). The approach is based on the idea of commanding sensor nodes on the aggregation paths to temporarily stop including their readings in the received aggregated readings from their upstream neighbors. The scheme is dependent on the ability of the sink to detect faulty nodes through changes in the received aggregated readings at the sink using a Markov Chain Controller (MCC). The algorithm that is run in the sink uses the MCC to assign a state to each sensor node based on transitions that are triggered by receiving aggregated path readings, and accordingly deduces the nodes that may be faulty. The experimental results show at least 98% detection rate at the cost of reasonable detection delays and generated wireless network traffic. Copyright © 2016 John Wiley & Sons, Ltd.     

无线传感器网络中数据汇聚方案的研究

针对分簇网络拓扑结构中簇头节点能量消耗过快,综合考虑了节点的密集程度和剩余能量,采用节点自适应的簇头选择算法,选择部署越集中和剩余能量越大的节点作为簇头节点。同时节点引入了新鲜性信息熵模型,通过比较前后两次接收到的数据的差别程度,设置一个参考阈值来判断是否转发数据。这种数据汇聚算法有效地降低了数据的冗余,减少了能量消耗,增加了带宽利用率,延长了网络的生存期。