无线传感器网络数据隐私保护技术

随着网络技术的飞速发展与无线传感器的普遍应用,保障数据传输的安全性与隐私性不受威胁,已成为人们日益关注的问题。据此,便从网络数据隐私保护的含义入手,并对无线传感器的数据隐私保护技术进行探究,以期为读者提供参考。     

无线传感器网络中的隐私保护研究

随着无线传感器网络的广泛应用,安全问题发生变化,通信安全成为重要的一部分,隐私保护日渐重要。首先分析了无线传感器网络的通信安全特点、通信安全的需求、面临的保密性威胁及攻击模型。最后,基于对无线传感器网络隐私保护问题的分析和评述,指出了今后该领域的研究方向。     

无线传感器网络中的隐私威胁与对策

随着无线传感器网络的应用深入到日常生活领域,如何保护隐私成为一个至关重要的问题.借助无线传感器网络,很容易收集个人信息.有的机构甚至把个人信息当作商品,进行收集、交换和出售,人们对这些行为越来越警觉,希望保护自己的隐私,隐私已成为无线传感嚣网络成功应用的一大障碍.如果没有提供适当的隐私保护,无线传感器网络就不能应用于这些领域.通过分析无线传感器网络的特点、面临的隐私威胁及相应的对策,基于通信系统一般化的物理模型,提出了一种隐私保护解决方案.     

无线传感器网络的位置隐私保护路由

当无线传感器网络用于监控敏感对象时,被监控对象的位置隐私成为一个关键问题。在传感节点发送的一连串信息,经过多跳,向基站报告一个监控对象时,敌手可以反向追踪信息源的位置。基于洪泛的幻影路由具有较小的安全期和较高的能耗。为了使敌手难于跳到跳地反向追踪传感节点通信的信号源,提出了基于定向随机步的幻影路由。在基于定向随机步的幻影路由中,每个消息都经历两个阶段：首先与基于洪泛的幻影路由一样,是一个随机步或定向步,随后是定向随机步直到基站。与基于洪泛的幻影路由相比,基于定向随机步的幻影路由明显具有较大的安全期和较低的能耗。     

无线传感器网络中的位置隐私保护

随着无线传感器网络的广泛应用,隐私成为无线传感器网络成功使用的主要障碍。当无线传感器网络用于监控敏感对象,被监控对象的位置隐私成为一个重要问题。在传感节点发送一系列分组,通过多跳,向基站报告监控对象时,敌手能够反向追踪分组到信息源位置。基于洪泛的幻影具有消息发送时间长且能量消耗过大的缺陷。为了保护能量受限的无线传感器网络中的位置隐私,提出了定向随机步。定向随机步使敌手难于跳到跳地反向追踪信息源。在定向随机步中,信源节点发出一个分组,此分组被单播给信源节点的父节点。当中介节点收到一个分组,它以等概率的方式转发给它的一个父节点。与基于洪泛的幻影相比,定向随机步具有较小的信息发送时间和较低的能量消耗。特别在中介节点具有多个父节点的情形下,定向随机步具有较大的安全期。     

面向隐私保护的无线传感器网络细粒度访问控制协议

针对无线传感器网络访问控制中的用户身份隐私保护和数据安全问题,提出了一种适用于多用户、隐私保护的访问控制协议。该协议采用属性基加密算法和分布式访问控制模式,使用属性证书、数字签名和门限机制,实现了用户的付费访问、细粒度访问控制和匿名访问,并保证了数据传输机密性和查询命令完整性。协议分析和协议比较表明,传感器节点的计算、存储和通信开销较小,方便实现用户和传感器节点动态加入,能更好地适应付费无线传感器网络的访问控制需求。     

无线传感器网络数据隐私保护技术

研究和解决数据隐私保护问题对无线传感器网络的大规模应用具有重要意义,同时无线传感器网络的特征使得数据隐私保护技术面临严重挑战.目前无线传感器网络数据隐私保护技术已成为研究热点,主要针对数据聚集、数据查询和访问控制中数据隐私保护问题进行了研究.文中对无线传感器网络数据隐私保护现有研究成果进行了总结,从数据操作任务和隐私保护实现技术两个维度对现有研究成果进行了分类,介绍了网络模型、攻击模型和安全目标,阐述了代表性协议的关键实现技术,分析和比较了代表性协议的性能并总结了各协议的主要优缺点,最后指出了未来的研究方向.     

面向隐私保护的无线传感器网络细粒度访问控制协议

针对无线传感器网络访问控制中的用户身份隐私保护和数据安全问题,提出了一种适用于多用户、隐私保护的访问控制协议。该协议采用属性基加密算法和分布式访问控制模式,使用属性证书、数字签名和门限机制,实现了用户的付费访问、细粒度访问控制和匿名访问,并保证了数据传输机密性和查询命令完整性。协议分析和协议比较表明,传感器节点的计算、存储和通信开销较小,方便实现用户和传感器节点动态加入,能更好地适应付费无线传感器网络的访问控制需求。     

电力物联网下无线传感器网络位置隐私保护方法研究

首先对无线传感器网络的概念及其在电力物联网中的应用进行了简单的介绍,指出了无线传感器网络中存在的隐私问题;其次针对位置隐私保护进行了概述,并给出了攻击者模型;接下来,分别介绍了几种源节点位置隐私保护和汇聚节点位置隐私保护技术,并对它们的性能进行了分析和比较;最后,我们对电力物联网中的无线传感器网络位置隐私保护技术所需考虑的问题提出了见解和建议.     

无线传感器网络位置隐私保护技术

对传感器网络位置隐私保护技术的研究现状与进展进行了综述,首先介绍网络模型、攻击模型和性能评价模型.接着,按照路径伪装、陷阱诱导、网络匿名和通信控制这4种策略对现有的研究成果进行了分类,阐述了代表性协议的核心技术.对各协议性能和优缺点的分析比较表明:4种策略都会在一定程度上影响网络的通信和能耗性能:路径伪装策略主要针对逐跳回溯攻击,网络匿名策略主要针对ID分析攻击,陷阱诱导和通信控制策略可以抵御多种类型的攻击.最后,对未来研究方向进行了展望.     

Quantum security in wireless sensor networks

Security in sensor networks, though an important issue for widely available wireless networks, has been studied less extensively than other properties of these networks, such as, for example, their reliability. The few security schemes proposed so far are based on classical cryptography. In contrast, the present paper develops a new security solution, based on quantum cryptography. The scheme developed here comes with the advantages quantum cryptography has over classical cryptography, namely, effectively unbreakable keys and therefore effectively unconditionally secure messages. Our security system ensures privacy of the measured data field in the presence of an intruder who listens to messages broadcast in the field.     

Location privacy and resilience in wireless sensor networks querying

Due to the wireless nature of communication in sensor networks, the communication patterns between sensors could be leaked regardless of the adoption of encryption mechanisms—those would just protect the message content. However, communication patterns could provide valuable information to an adversary. For instance, this is the case when sensors reply to a query broadcast by a Base Station (BS); an adversary eavesdropping the communication traffic could realize which sensors are the ones that possibly match the query (that is, the ones that replied). This issue is complicated by the severe resource constrained environment WSNs are subject to, that call for efficient and scalable solutions.In this paper, we have addressed the problem of preserving the location privacy of the sensors of a wireless sensor network when they send a reply to a query broadcast by the BS. In particular, we deal with one of the worst scenarios for privacy: When sensors are queried by a BS to provide the MAX of their stored readings. We provide a probabilistic and scalable protocol to compute the MAX that enjoys the following features: (i) it guarantees the location privacy of the sensors replying to the query; (ii) it is resilient to an active adversary willing to alter the readings sent by the sensors; and, (iii) it allows to trade-off the accuracy of the result with (a small) overhead increase. Finally, extensive simulations support our analysis, showing the quality of our proposal.     

WSNs中的位置隐私评述

随着无线传感器网络（WSNs）的广泛应用,隐私已成为WSNs成功应用的一大障碍。当WSNs用于监控敏感对象,被监控对象的位置隐私成为一个重要问题。特别是WSNs在军事上的应用,基站一旦被控制或破坏,后果不堪设想。分析了WSNs的安全特点、位置隐私性能评价、面临的隐私威胁,并基于对WSNs位置隐私问题的分析和评述,指出了今后该领域的研究方向。     

Protecting the sink location privacy in wireless sensor networks

Wireless sensor networks (WSNs) are widely deployed to collect data in military and civilian applications today. Due to the open nature of a WSN, it is relatively easy for an adversary to eavesdrop and trace packets in order to capture the receiver. Therefore, location privacy, particularly the location privacy of the sink node, requires ultimate protection because of its critical position in WSNs. In this paper, we propose a sink location privacy protection scheme by injecting fake packets, but every real packet is still routed along its shortest path. The fake packets are routed to some random destinations and some fake sinks in order to provide the path diversity. It is difficult for an attacker to distinguish the real packets from the fake packets. Thus, the chance of finding the real sink by packet-tracing attack is reduced. Privacy analysis shows that the sink location privacy can be protected better with higher successful probability. We examine the packet travel delay, safe time, and energy consumption by both mathematical analysis and simulations.     

The price of security in wireless sensor networks

With the increased application of wireless sensor networks (WSNs) to military, commercial, and home environments, securing the data in the network has become a critical issue. Several security mechanisms, such as TinySec, have been introduced to address the need for security in WSNs. The cost of security, however, still mostly remains an unknown variable. To provide a better understanding of this cost we have studied three aspects of WSNs security: encryption algorithms, modes of operation for block ciphers, and message authentication algorithms. We have measured and compared their memory and energy consumption on both MicaZ and TelosB sensor motes. The results of our experiments provide insight into the suitability of different security algorithms for use in WSN environments and could be used by WSN designers to construct the security architecture of their systems in a way that both satisfies the requirements of the application and reasonably uses the constrained sensor resources.     

无线传感器网络的体系结构和应用安全

随着物联网应用领域的不断扩大,无线传感器网络的应用也以前所未有的速度迅速拓展。无线传感器网络(WSN)具有覆盖区域广泛、检测精度高、可以远程监控和高容错性等优点,使其在军事、工业、农业、环境保护、医疗系统、智能交通等各领域得到了广泛的应用。虽然无线传感器网络的应用前景非常广泛,但仍存在很多技术问题需要解决,包括最大限度减少传感节点的功耗,以及如何有效提高网络系统容量、减少碰撞阻塞等。为了有效解决以上技术难题,通过对MSN的体系结构以及具体应用领域的研究,提出了解决办法。     

无线传感器网络中的跨层安全设计

无线传感器网络(WSNs)发展迅速,可广泛应用于军事、工业及科学等领域。传感器网络在无线信道中工作,其节点有限的能源、计算能力、存储能力使得其面临着严重的安全问题。已提出的许多安全方法都基于分层设计的概念。分析了分层安全设计的局限性,回顾了现存的W SNs的安全设计方案,提出了一些新的跨层解决办法,并指出了传感器网络中跨层安全的研究方向。     

A security policy language for wireless sensor networks

Authenticated computer system users are only authorized to access certain data within the system. In the future, wireless sensor networks (WSNs) will need to restrict access to data as well. To date, WSN security has largely been based on encryption and authentication schemes. The WSN Authorization Specification Language (WASL) is a mechanism-independent composable WSN policy language that can specify arbitrary and composable security policies that are able to span and integrate multiple WSN policies. Using WASL, a multi-level security policy for a 1000 node network requires only 60 bytes of memory per node.