Collaborative Location Certification for Sensor Networks

被引:2
|
作者
Gao, Jie [1 ]
Sion, Radu [1 ]
Lederer, Sol [1 ]
机构
[1] SUNY Stony Brook, Dept Comp Sci, Network Secur & Appl Cryptog Lab, Stony Brook, NY 11794 USA
关键词
Algorithms; Systems; sensor networks; security; location certification; LOCALIZATION;
D O I
10.1145/1777406.1777409
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Location information is of essential importance in sensor networks deployed for generating location-specific event reports. When such networks operate in hostile environments, it becomes imperative to guarantee the correctness of event location claims. In this article we address the problem of assessing location claims of untrusted (potentially compromised) nodes. The mechanisms introduced here prevent a compromised node from generating illicit event reports for locations other than its own. This is important because by compromising "easy target" sensors (say, sensors on the perimeter of the field that's easier to access), the adversary should not be able to impact data flows associated with other ("premium target") regions of the network. To achieve this goal, in a process we call location certification, data routed through the network is "tagged" by participating nodes with "belief" ratings, collaboratively assessing the probability that the claimed source location is indeed correct. The effectiveness of our solution relies on the joint knowledge of participating nodes to assess the truthfulness of claimed locations. By collaboratively generating and propagating a set of "belief" ratings with transmitted data and event reports, the network allows authorized parties (e.g., final data sinks) to evaluate a metric of trust for the claimed location of such reports. Belief ratings are derived from a data model of observed past routing activity. The solution is shown to feature a strong ability to detect false location claims and compromised nodes. For example, incorrect claims as small as 2 hops (from the actual location) are detected with over 90% accuracy. Finally, these new location certification mechanisms can be deployed in tandem with traditional secure localization, yet do not require it, and, in a sense, can serve to minimize the need thereof.
引用
收藏
页码:1 / 26
页数:26
相关论文
共 50 条
  • [31] Collaborative Sensor Networks with Bayesian Multitarget Tracking and Sensor Localization
    Jajamovich, Guido H.
    Wang, Xiaodong
    MILCOM 2009 - 2009 IEEE MILITARY COMMUNICATIONS CONFERENCE, VOLS 1-4, 2009, : 2300 - 2304
  • [32] A novel collaborative approach for location prediction in mobile networks
    Sepahkar, Mehdi
    Khayyambashi, Mohammad Reza
    WIRELESS NETWORKS, 2018, 24 (01) : 283 - 294
  • [33] A novel collaborative approach for location prediction in mobile networks
    Mehdi Sepahkar
    Mohammad Reza Khayyambashi
    Wireless Networks, 2018, 24 : 283 - 294
  • [34] Stochastic Collaborative Beamforming in Wireless Sensor Networks
    Navarro-Camba, Enrique A.
    Felici-Castell, Santiago
    Perez-Solano, Juan J.
    Segura-Garcia, Jaume
    Garcia-Pineda, Miguel
    Pastor-Aparicio, Adolfo
    PROCEEDINGS OF THE EURO AMERICAN CONFERENCE ON TELEMATICS AND INFORMATION SYSTEMS (EATIS '18), 2018,
  • [35] Towards a collaborative model for Wireless Sensor Networks
    de Brito, Lina M. Pestana Leao
    Peralta, Laura M. Rodriguez
    Reis, Mauricio D. Luis
    PERVASIVE COLLABORATIVE NETWORKS, 2008, 283 : 371 - 380
  • [36] Collaborative Data Transmission in Wireless Sensor Networks
    Berbakov, Lazar
    Dimic, Goran
    Beko, Marko
    Vasiljevic, Jelena
    Stojkovic, Zeljko
    IEEE ACCESS, 2020, 8 : 39647 - 39658
  • [37] Collaborative resource allocation in wireless sensor networks
    Giannecchini, S
    Caccamo, M
    Shih, CS
    16TH EUROMICRO CONFERENCE ON REAL-TIME SYSTEMS, PROCEEDINGS, 2004, : 35 - 44
  • [38] Collaborative Synchronization for Signal Reinforcement in Sensor Networks
    Fleming, Todd B.
    Athanas, Peter M.
    AD HOC & SENSOR WIRELESS NETWORKS, 2007, 4 (03) : 179 - 198
  • [39] Distribution strategies for collaborative and adaptive sensor networks
    Horling, B
    Lesser, V
    2005 INTERNATIONAL CONFERENCE ON INTEGRATION OF KNOWLEDGE INTENSIVE MULTI-AGENT SYSTEMS: KIMAS'05: MODELING, EXPLORATION, AND ENGINEERING, 2005, : 497 - 504
  • [40] Collaborative target localization in camera sensor networks
    Liu, Liang
    Ma, Huadong
    Zhang, Xi
    WCNC 2008: IEEE WIRELESS COMMUNICATIONS & NETWORKING CONFERENCE, VOLS 1-7, 2008, : 2403 - 2407