无线传感器网络中安全数据收集的研究
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摘要
无线传感器网络(Wireless Sensor Networks,简称WSNs)已经成为电子、计算机、控制等多个领域的研究热点,广泛应用于军事、工业以及科研等领域。近年来,发展物联网技术已成为我国重要的战略方向,无线传感器网络作为物联网的基本组成部分,随着应用越来越广泛,其安全问题已成为业界关注的焦点。
本论文把整个数据收集过程分为三个阶段：门限加密阶段、随机分散路由阶段和正常路由阶段。
首先,本论文提出了基于信任模型的随机分散路由算法。数据在无线传感器网络中路由时,经常会受到多种形式的攻击,常见的有拒绝服务(Denial of Service,简称DoS)攻击、节点损坏攻击和节点复制攻击,导致基站无法接收到正确数据,甚至根本无法接收到数据。而本论文提出的路由算法在数据路由过程中增加了路径选择的不确定性,再加上节点行为信任模型的建立,大大增加了敌人攻击的难度,因此能有效抵御DoS攻击、节点损坏攻击和节点复制攻击。
其次,本论文提出了基于目击者直接投票模型的数据保障算法。在正常路由阶段,数据也可能被敌方截获或破坏。如果出现这种情况,基站便会错误地把损坏数据当正确数据使用,这将给整个系统带来巨大的安全威胁,甚至会浪费之前路由过程所做的全部工作。目击者直接投票模型在基站之前加入一些融合节点,数据经融合节点决策并投票后再发送给基站,最后由基站决定是否接收融合结果以及接收哪个融合结果。
最后,对未来工作进行了探讨和展望。本论文提出的算法,能有效抵御无线传感器网络的主要攻击手段,同时能提高数据传输效率,从而延长网络生命期,对无线传感器网络数据安全技术的相关研究有一定的参考价值。
Wireless Sensor Networks (WSNs) have become the research hotspot of electronic, computer, control, and other areas. They are widely used in military, industry, and scientific research. In recent years, the development of Internet of Things has been upgraded to a significant strategic direction. WSN is an essential part of Internet of Things, and its security has become the focus of the industry.
In this thesis, the data collection process is divided into three phases: threshold encryption phase, randomized dispersive routing phase and normal routing phase.
First, this thesis proposes a randomized dispersive routing algorithm based on trust model. Data routing in WSNs always suffers from a wide variety of attacks, such as denial-of-service (DoS) attack, compromised-node attack and node-replication attack. All these attacks result in that the base station cannot receive the correct data, or even cannot receive data radically. By raising the uncertainty of path selection and building the trust model of node behavior, the routing algorithm proposed in this thesis greatly increases the difficulty of the enemy attack. It can effectively resist the DoS attack, compromised-node attack and node-replication attack.
Second, this thesis proposes the data assurance mechanism based on witness direct-voting model. In normal routing phase, data may also be intercepted or destroyed by the enemy, while the base station does not know that. If this occurs, the base station would not receive the correct data, but wrong data instead, which will bring the whole system a huge security threat, or even waste all the work done in the routing phases. This mechanism put some additional fusion nodes in front of base station. After decision-making and direct-voting of those fusion nodes, base station will decide which fusion results to receive, or may reject all of them.
Finally, future work is discussed and prospected. The proposed algorithms can effectively resist main attacks in WSNs, improve data transmission efficiency simultaneously, and thereby prolong the network lifetime. They also have some reference value in security technology research of WSNs.
本论文把整个数据收集过程分为三个阶段：门限加密阶段、随机分散路由阶段和正常路由阶段。
首先,本论文提出了基于信任模型的随机分散路由算法。数据在无线传感器网络中路由时,经常会受到多种形式的攻击,常见的有拒绝服务(Denial of Service,简称DoS)攻击、节点损坏攻击和节点复制攻击,导致基站无法接收到正确数据,甚至根本无法接收到数据。而本论文提出的路由算法在数据路由过程中增加了路径选择的不确定性,再加上节点行为信任模型的建立,大大增加了敌人攻击的难度,因此能有效抵御DoS攻击、节点损坏攻击和节点复制攻击。
其次,本论文提出了基于目击者直接投票模型的数据保障算法。在正常路由阶段,数据也可能被敌方截获或破坏。如果出现这种情况,基站便会错误地把损坏数据当正确数据使用,这将给整个系统带来巨大的安全威胁,甚至会浪费之前路由过程所做的全部工作。目击者直接投票模型在基站之前加入一些融合节点,数据经融合节点决策并投票后再发送给基站,最后由基站决定是否接收融合结果以及接收哪个融合结果。
最后,对未来工作进行了探讨和展望。本论文提出的算法,能有效抵御无线传感器网络的主要攻击手段,同时能提高数据传输效率,从而延长网络生命期,对无线传感器网络数据安全技术的相关研究有一定的参考价值。
Wireless Sensor Networks (WSNs) have become the research hotspot of electronic, computer, control, and other areas. They are widely used in military, industry, and scientific research. In recent years, the development of Internet of Things has been upgraded to a significant strategic direction. WSN is an essential part of Internet of Things, and its security has become the focus of the industry.
In this thesis, the data collection process is divided into three phases: threshold encryption phase, randomized dispersive routing phase and normal routing phase.
First, this thesis proposes a randomized dispersive routing algorithm based on trust model. Data routing in WSNs always suffers from a wide variety of attacks, such as denial-of-service (DoS) attack, compromised-node attack and node-replication attack. All these attacks result in that the base station cannot receive the correct data, or even cannot receive data radically. By raising the uncertainty of path selection and building the trust model of node behavior, the routing algorithm proposed in this thesis greatly increases the difficulty of the enemy attack. It can effectively resist the DoS attack, compromised-node attack and node-replication attack.
Second, this thesis proposes the data assurance mechanism based on witness direct-voting model. In normal routing phase, data may also be intercepted or destroyed by the enemy, while the base station does not know that. If this occurs, the base station would not receive the correct data, but wrong data instead, which will bring the whole system a huge security threat, or even waste all the work done in the routing phases. This mechanism put some additional fusion nodes in front of base station. After decision-making and direct-voting of those fusion nodes, base station will decide which fusion results to receive, or may reject all of them.
Finally, future work is discussed and prospected. The proposed algorithms can effectively resist main attacks in WSNs, improve data transmission efficiency simultaneously, and thereby prolong the network lifetime. They also have some reference value in security technology research of WSNs.
引文
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[3]K. Pister, B. Hohlt, J. Jeong, et al. Ivy A Sensor Network Infrastructure [EB/OL]. http://www-bsac.eecs.berkeley.edu/projects/ivy.2003
[4]D. Estrin, R. Govindan, J. Heidemann. Next Century Challenges:Scalable Coordination in Sensor Networks [C]. In:Proceedings of the Fifth Annual International Conference on Mobile Computing and Networks (MobiCOM'99), Washington, USA,1999:263-270
[5]J. Agre, L. Clare. An Integrated Architecture for Cooperative Sensing Networks [J]. IEEE Computer Magazine,2000,33(5):106-108
[6]ALERT [EB/OL]. http://www.altersystem.org
[7]P. Bonnet, J. Gehrke, P. Seshadri. Querying the Physical World [J]. IEEE Personal Communication,2000,7(5):10-15
[8]N. Noury, T. Herve, V. Rialle, et al. Monitoring Behavior in Home Using a Smart Fall Sensor [C]. In:Proceedings of the IEEE-EMBS Special Topic Conference on Micro-technologies in Medicine and Biology. Lyon:IEEE Computer Society, 2000:607-610
[9]Sensor Webs [EB/OL]. http://sensorwebs.jpl.nasa.gov/
[10]E. Shih, S. Cho, N. Ickes, et al. Physical Layer Driven Protocol and Algorithm Design for Energy-efficient Wireless Sensor Networks [C]. In:Proceedings of the ACM MobiCom 2001. Rome:ACM Press,2001:272-286
[11]孙利民,李建中,陈渝.无线传感器网络[M].北京：清华大学出版社,2005.3-7
[12]文戈.无线传感器网络中基于Voronoi图的覆盖与连通综合管理协议[硕士学位论文].长沙：中南大学,2007
[13]M. Cardei and J. Wu. Coverage in Wireless Sensor Networks [M]. M. IIyas and I. Magboub, eds. Handbook of Sensor Networks. CRC Press,2004
[14]D. Zorbas, D. Glynos, P. Kotzanikolaou, et al. Solving Coverage Problems in Wireless Sensor Networks Using Cover Sets [J]. Ad Hoc Networks,2010,8(4): 400-415
[15]田莹,张淑芳,王莹.无线传感器网络分布式概率覆盖保持协议[J].通信学报,2009,30(1)：70-75
[16]X. Bai, S. Kumar, D. Xuan, et al. Deploying Wireless Sensors to Achieve both Coverage and Connectivity [C]. In:Proceedings of the 7th ACM International Symposium on Mobile Ad Hoc Networking and Computing, May 2006:131-142
[17]蒋杰,方力,张鹤颖,窦文华.无线传感器网络最小连通覆盖集问题求解算法[J].软件学报,2005,17(2)：175-184
[18]S. Slijepcevic and M. Potkonjak. Power Efficient Organization of Wireless Sensor Networks [C]. In:Proceedings of International Conference on Communications (ICC 2001), June 2001:472-476
[19]Y. Zhou, Y. Fang, and Y. Zhang. Securing Wireless Sensor Networks:A Survey [J]. IEEE Communications Surveys and Tutorials,2008, (10):6-28
[20]A. Perrig, R. Szewczyk, V. Wen, et al. SPINS:Security Protocols for Sensor Networks [J]. ACM Wireless Networks, Sept.2002,8(5):521-534
[21]T. Kavitha, D. Sridharan. Security Vulnerabilities in Wireless Sensor Networks:A Survey [J]. Journal of Information Assurance and Security,2010, (5):31-44
[22]H. Chan and A. Perrig. Security and Privacy in Sensor Networks [J]. IEEE Computer,2003,36(10):103-105
[23]A. Perrig, J. Stankovic, and D. Wagner. Security in Wireless Sensor Networks [J]. Communications of the ACM,2004,47(6):53-57
[24]L. Eschenauer and V. D. Gligor. A Key-management Scheme for Distributed Sensor Networks [C]. In:Proceedings of the 9th ACM Conference on Computer and Communications Security (CCS2002). Washington:ACM Press, Nov.2002: 41-47
[25]H. Chan, A. Perrig, and D. Song. Random Key Predistribution Schemes for Sensor Networks [C]. In:Proceedings of the IEEE 2003 Symposium on Research in Security and Privacy. Berkeley, CA:IEEE Computer Society,2003:197-213
[26]G. Jolly, Kuscu M C, Kokate P, et al. A Low-energy Key Management Protocol for Wireless Sensor Network [C]. In:Proceedings of the Eighth IEEE Intl. Symposium on Computers and Communication (ISCC'03). Turkey:July 2003, (1):335-340
[27]D. Carman, P. Kruus, and B. Matt. Constraints and Approaches for Distributed Sensor Network Security [R]. NAI Labs, September 2000:1-26
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