The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform

Lionel M Ni - One of the best experts on this subject based on the ideXlab platform.

  • learning adaptive temporal radio maps for Signal Strength based location estimation
    IEEE Transactions on Mobile Computing, 2008
    Co-Authors: Qiang Yang, Lionel M Ni
    Abstract:

    In wireless networks, a client's locations can be estimated using the Signals received from various Signal transmitters. Static fingerprint-based techniques are commonly used for location estimation, in which a radio map is built by calibrating Signal-Strength values in the offline phase. These values, compiled into deterministic or probabilistic models, are used for online localization. However, the radio map can be outdated when the Signal-Strength values change with time due to environmental dynamics, and repeated data calibration is infeasible or expensive. In this paper, we present a novel algorithm, known as LEMT (Location Estimation using Model Trees), to reconstruct a radio map using real-time Signal- Strength readings received at the reference points. This algorithm can take into account real-time Signal-Strength values at each time point and make use of the dependency between the estimated locations and reference points. We show that this technique can effectively accommodate the variations of Signal Strength over different time periods without the need to rebuild the radio maps repeatedly. We demonstrate the effectiveness of our proposed technique on realistic data sets collected from an 802.11b wireless network and a RFID-based network.

Xiuyuan Zheng - One of the best experts on this subject based on the ideXlab platform.

  • Achieving robust wireless localization resilient to Signal Strength attacks
    Wireless Networks, 2011
    Co-Authors: Yingying Chen, Jie Yang, Xiuyuan Zheng
    Abstract:

    Received Signal Strength (RSS) based algorithms have been very attractive for localization since they allow the reuse of existing communication infrastructure and are applicable to many commodity radio technologies. Such algorithms, however, are sensitive to a set of non-cryptographic attacks, where the physical measurement process itself can be corrupted by adversaries. For example, the attacker can perform Signal Strength attacks by placing an absorbing or reflecting material around a wireless device to modify its RSS readings. In this work, we first formulate the all-around Signal Strength attacks, where similar attacks are launched towards all landmarks, and experimentally show the feasibility of launching such attacks. We then propose a general principle for designing RSS-based algorithms so that they are robust to all-around Signal Strength attacks. To evaluate our approach, we adapt a set of representative RSS-based localization algorithms according to our principle. We experiment with both simulated attacks and two sets of real attack scenarios. All the experiments show that our design principle can be applied to a wide spectrum of algorithms to achieve comparable performance with much better robustness.

  • INFOCOM - Designing localization algorithms robust to Signal Strength attacks
    2011 Proceedings IEEE INFOCOM, 2011
    Co-Authors: Yingying Chen, Jie Yang, Xiuyuan Zheng
    Abstract:

    Received Signal Strength (RSS) based localization algorithms are sensitive to a set of non-cryptographic attacks. For example, the attacker can perform Signal Strength attacks by placing an absorbing or reflecting material around a wireless device to modify its RSS readings. In this work, we first formulate the all-around Signal Strength attacks, where similar attacks are launched towards all landmarks, and experimentally show the feasibility of launching such attacks. We then propose a general principle for designing RSS-based algorithms so that they are robust to all-around Signal Strength attacks. To evaluate our approach, we adapt two RSS-based localization algorithms according to our principle and experiment with real attack scenarios. All the experiments show that our design principle can be applied to achieve comparable performance with much better robustness.

Yingying Chen - One of the best experts on this subject based on the ideXlab platform.

  • Achieving robust wireless localization resilient to Signal Strength attacks
    Wireless Networks, 2011
    Co-Authors: Yingying Chen, Jie Yang, Xiuyuan Zheng
    Abstract:

    Received Signal Strength (RSS) based algorithms have been very attractive for localization since they allow the reuse of existing communication infrastructure and are applicable to many commodity radio technologies. Such algorithms, however, are sensitive to a set of non-cryptographic attacks, where the physical measurement process itself can be corrupted by adversaries. For example, the attacker can perform Signal Strength attacks by placing an absorbing or reflecting material around a wireless device to modify its RSS readings. In this work, we first formulate the all-around Signal Strength attacks, where similar attacks are launched towards all landmarks, and experimentally show the feasibility of launching such attacks. We then propose a general principle for designing RSS-based algorithms so that they are robust to all-around Signal Strength attacks. To evaluate our approach, we adapt a set of representative RSS-based localization algorithms according to our principle. We experiment with both simulated attacks and two sets of real attack scenarios. All the experiments show that our design principle can be applied to a wide spectrum of algorithms to achieve comparable performance with much better robustness.

  • INFOCOM - Designing localization algorithms robust to Signal Strength attacks
    2011 Proceedings IEEE INFOCOM, 2011
    Co-Authors: Yingying Chen, Jie Yang, Xiuyuan Zheng
    Abstract:

    Received Signal Strength (RSS) based localization algorithms are sensitive to a set of non-cryptographic attacks. For example, the attacker can perform Signal Strength attacks by placing an absorbing or reflecting material around a wireless device to modify its RSS readings. In this work, we first formulate the all-around Signal Strength attacks, where similar attacks are launched towards all landmarks, and experimentally show the feasibility of launching such attacks. We then propose a general principle for designing RSS-based algorithms so that they are robust to all-around Signal Strength attacks. To evaluate our approach, we adapt two RSS-based localization algorithms according to our principle and experiment with real attack scenarios. All the experiments show that our design principle can be applied to achieve comparable performance with much better robustness.

  • A security and robustness performance analysis of localization algorithms to Signal Strength attacks
    ACM Transactions on Sensor Networks, 2009
    Co-Authors: Yingying Chen, Konstantinos Kleisouris, Wade Trappe, Richard P. Martin
    Abstract:

    Recently, it has been noted that localization algorithms that use Signal Strength are susceptible to noncryptographic attacks, which consequently threatens their viability for sensor applications. In this work, we examine several localization algorithms and evaluate their robustness to attacks where an adversary attenuates or amplifies the Signal Strength at one or more landmarks. We study both point-based and area-based methods that employ received Signal Strength for localization, and propose several performance metrics that quantify the estimator's precision, bias, and error, including Holder metrics, which quantify the variability in position space for a given variability in Signal Strength space. We then conduct a trace-driven evaluation of a set of representative algorithms, where we measured their performance as we applied attacks on real data from two different buildings. We found the median error degraded gracefully, with a linear response as a function of the attack Strength. We also found that area-based algorithms experienced a decrease and a spatial-shift in the returned area under attack, implying that precision increases though bias is introduced for these schemes. Additionally, we observed similar values for the average Holder metric across most of the algorithms, thereby providing strong experimental evidence that nearly all the algorithms have similar average responses to Signal Strength attacks with the exception of the Bayesian Networks algorithm.

Parameshwaran Krishnan - One of the best experts on this subject based on the ideXlab platform.

  • INFOCOM - On the accuracy of Signal Strength-based estimation techniques
    Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies., 1
    Co-Authors: Anjur Sundaresan Krishnakumar, Parameshwaran Krishnan
    Abstract:

    In this paper, we address the problem of finding the inherent uncertainty of Signal Strength-based location estimation techniques. We propose a mathematical model for mapping uncertainty in Signal Strength space to uncertainty in physical space. We then analyze this model to compute the minimum value of the uncertainty in location estimation using Signal Strength measurements. The results of this analysis are used to draw conclusions about the dependence of the minimum uncertainty of various factors such as the Signal variance, number of APs, distance between the APs and the propagation constant. We provide an argument linking the minimum uncertainty with a lower limit on the median error in location estimation using classification techniques.

Qiang Yang - One of the best experts on this subject based on the ideXlab platform.

  • learning adaptive temporal radio maps for Signal Strength based location estimation
    IEEE Transactions on Mobile Computing, 2008
    Co-Authors: Qiang Yang, Lionel M Ni
    Abstract:

    In wireless networks, a client's locations can be estimated using the Signals received from various Signal transmitters. Static fingerprint-based techniques are commonly used for location estimation, in which a radio map is built by calibrating Signal-Strength values in the offline phase. These values, compiled into deterministic or probabilistic models, are used for online localization. However, the radio map can be outdated when the Signal-Strength values change with time due to environmental dynamics, and repeated data calibration is infeasible or expensive. In this paper, we present a novel algorithm, known as LEMT (Location Estimation using Model Trees), to reconstruct a radio map using real-time Signal- Strength readings received at the reference points. This algorithm can take into account real-time Signal-Strength values at each time point and make use of the dependency between the estimated locations and reference points. We show that this technique can effectively accommodate the variations of Signal Strength over different time periods without the need to rebuild the radio maps repeatedly. We demonstrate the effectiveness of our proposed technique on realistic data sets collected from an 802.11b wireless network and a RFID-based network.