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

  • optimal denial of service attack scheduling with Energy Constraint
    IEEE Transactions on Automatic Control, 2015
    Co-Authors: Heng Zhang, Ling Shi, Peng Cheng, Jiming Chen
    Abstract:

    Security of Cyber-Physical Systems (CPS) has gained increasing attention in recent years. Most existing works mainly investigate the system performance given some attacking patterns. In this technical note, we investigate how an attacker should schedule its Denial-of-Service (DoS) attacks to degrade the system performance. Specifically, we consider the scenario where a sensor sends its data to a remote estimator through a wireless channel, while an Energy-constrained attacker decides whether to jam the channel at each sampling time. We construct optimal attack schedules to maximize the expected average estimation error at the remote estimator. We also provide the optimal attack schedules when a special intrusion detection system (IDS) at the estimator is given. We further discuss the optimal attack schedules when the sensor has Energy Constraint. Numerical examples are presented to demonstrate the effectiveness of the proposed optimal attack schedules.

  • an online sensor power schedule for remote state estimation with communication Energy Constraint
    IEEE Transactions on Automatic Control, 2014
    Co-Authors: Peng Cheng, Jiming Chen
    Abstract:

    We consider sensor transmission power scheduling for remote state estimation with limited communication Energy. A sensor needs to decide when to switch between different transmission Energy levels in order to minimize the average expected estimation error covariance subject to the available Energy budget. In the existing work the sensor only exploits the prior knowledge of the system parameters, the noise covariance and the channel characteristics but neglects the realtime information the estimator can provide. Thanks to the power asymmetry between the sensor and the estimator, we propose an online scheduling scheme which makes a choice based on the acknowledgement sequence at the remote estimator side and show that the scheme outperforms the optimal offline schedule under the same Energy Constraint.

  • Optimal Periodic Sensor Schedule for Steady-State Estimation Under Average Transmission Energy Constraint
    IEEE Transactions on Automatic Control, 2013
    Co-Authors: Zhu Ren, Ling Shi, Peng Cheng, Jiming Chen, Youxian Sun
    Abstract:

    We consider periodic sensor scheduling for remote state estimation under average transmission Energy Constraint. The sensor decides whether or not to send its data to a remote estimator in order to meet the transmission Energy Constraint. The transmitted data are likely to be dropped due to the imperfect communication. An optimal periodic schedule is found via the tools from the Markov chain. Furthermore, a sufficient condition of the system dynamics, Energy budget, and packet drop rate, under which the remote estimator is guaranteed to be stable, is derived. Examples are provided to show the effectiveness of results.

  • Brief paper: Sensor data scheduling for optimal state estimation with communication Energy Constraint
    Automatica, 2011
    Co-Authors: Ling Shi, Peng Cheng, Jiming Chen
    Abstract:

    In this paper, we consider sensor data scheduling with communication Energy Constraint. A sensor has to decide whether to send its data to a remote estimator or not due to the limited available communication Energy. We construct effective sensor data scheduling schemes that minimize the estimation error and satisfy the Energy Constraint. Two scenarios are studied: the sensor has sufficient computation capability and the sensor has limited computation capability. For the first scenario, we are able to construct the optimal scheduling scheme. For the second scenario, we are able to provide lower and upper bounds of the minimum error and construct a scheduling scheme whose estimation error falls within the bounds.

Ling Shi - One of the best experts on this subject based on the ideXlab platform.

  • optimal denial of service attack scheduling with Energy Constraint over packet dropping networks
    IEEE Transactions on Automatic Control, 2018
    Co-Authors: Jiahu Qin, Ling Shi
    Abstract:

    The recent years have seen a surge of security issues of cyber-physical systems (CPS). In this paper, denial-of-service (DoS) attack scheduling is investigated in depth. Specifically, we consider a system where a remote estimator receives the data packet sent by a sensor over a wireless network at each time instant, and an Energy-constrained attacker that cannot launch DoS attacks all the time designs the optimal DoS attack scheduling to maximize the attacking effect on the remote estimation performance. Most of the existing works concerning DoS attacks focus on the ideal scenario in which data packets can be received successfully if there is no DoS attack. To capture the unreliability nature of practical networks, we study the packet-dropping network in which packet dropouts may occur even in the absence of attack. We derive the optimal attack scheduling scheme that maximizes the average expected estimation error, and the one which maximizes the expected terminal estimation error over packet-dropping networks. We also present some countermeasures against DoS attacks, and discuss the optimal defense strategy, and how the optimal attack schedule can serve for more effective and resource-saving countermeasures. We further investigate the optimal attack schedule with multiple sensors. The optimality of the theoretical results is demonstrated by numerical simulations.

  • optimal denial of service attack scheduling with Energy Constraint
    IEEE Transactions on Automatic Control, 2015
    Co-Authors: Heng Zhang, Ling Shi, Peng Cheng, Jiming Chen
    Abstract:

    Security of Cyber-Physical Systems (CPS) has gained increasing attention in recent years. Most existing works mainly investigate the system performance given some attacking patterns. In this technical note, we investigate how an attacker should schedule its Denial-of-Service (DoS) attacks to degrade the system performance. Specifically, we consider the scenario where a sensor sends its data to a remote estimator through a wireless channel, while an Energy-constrained attacker decides whether to jam the channel at each sampling time. We construct optimal attack schedules to maximize the expected average estimation error at the remote estimator. We also provide the optimal attack schedules when a special intrusion detection system (IDS) at the estimator is given. We further discuss the optimal attack schedules when the sensor has Energy Constraint. Numerical examples are presented to demonstrate the effectiveness of the proposed optimal attack schedules.

  • Optimal Periodic Sensor Schedule for Steady-State Estimation Under Average Transmission Energy Constraint
    IEEE Transactions on Automatic Control, 2013
    Co-Authors: Zhu Ren, Ling Shi, Peng Cheng, Jiming Chen, Youxian Sun
    Abstract:

    We consider periodic sensor scheduling for remote state estimation under average transmission Energy Constraint. The sensor decides whether or not to send its data to a remote estimator in order to meet the transmission Energy Constraint. The transmitted data are likely to be dropped due to the imperfect communication. An optimal periodic schedule is found via the tools from the Markov chain. Furthermore, a sufficient condition of the system dynamics, Energy budget, and packet drop rate, under which the remote estimator is guaranteed to be stable, is derived. Examples are provided to show the effectiveness of results.

  • Brief paper: Sensor data scheduling for optimal state estimation with communication Energy Constraint
    Automatica, 2011
    Co-Authors: Ling Shi, Peng Cheng, Jiming Chen
    Abstract:

    In this paper, we consider sensor data scheduling with communication Energy Constraint. A sensor has to decide whether to send its data to a remote estimator or not due to the limited available communication Energy. We construct effective sensor data scheduling schemes that minimize the estimation error and satisfy the Energy Constraint. Two scenarios are studied: the sensor has sufficient computation capability and the sensor has limited computation capability. For the first scenario, we are able to construct the optimal scheduling scheme. For the second scenario, we are able to provide lower and upper bounds of the minimum error and construct a scheduling scheme whose estimation error falls within the bounds.

Jae Hong Lee - One of the best experts on this subject based on the ideXlab platform.

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

  • distributed censoring with Energy Constraint in wireless sensor networks
    International Conference on Acoustics Speech and Signal Processing, 2018
    Co-Authors: Liu Yang, Hongbin Zhu, Kai Kang, Xiliang Luo, Hua Qian, Yang Yang
    Abstract:

    In wireless sensor networks (WSN s), Energy is always precious for sensor nodes. To save Energy, censoring is introduced to cut the total number of transmission by only transmitting informative data. This algorithm, however, ignores the Energy consumption during the delivery of parameters, which can be significant comparing to the saved power. In this paper, we consider the adaptive censoring from the Energy perspective. A distributed censoring algorithm with Energy Constraint is developed that allows sensor nodes to make autonomous decisions on whether to transmit the incoming data. We show that with the proposed algorithm, the overall Energy consumption of the WSN s is reduced, while the performance loss in terms of the estimation error is negligible. Simulation results validate its effectiveness.

  • ICASSP - Distributed Censoring with Energy Constraint in Wireless Sensor Networks
    2018 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2018
    Co-Authors: Liu Yang, Hongbin Zhu, Kai Kang, Xiliang Luo, Hua Qian, Yang Yang
    Abstract:

    In wireless sensor networks (WSN s), Energy is always precious for sensor nodes. To save Energy, censoring is introduced to cut the total number of transmission by only transmitting informative data. This algorithm, however, ignores the Energy consumption during the delivery of parameters, which can be significant comparing to the saved power. In this paper, we consider the adaptive censoring from the Energy perspective. A distributed censoring algorithm with Energy Constraint is developed that allows sensor nodes to make autonomous decisions on whether to transmit the incoming data. We show that with the proposed algorithm, the overall Energy consumption of the WSN s is reduced, while the performance loss in terms of the estimation error is negligible. Simulation results validate its effectiveness.

Peng Cheng - One of the best experts on this subject based on the ideXlab platform.

  • optimal denial of service attack scheduling with Energy Constraint
    IEEE Transactions on Automatic Control, 2015
    Co-Authors: Heng Zhang, Ling Shi, Peng Cheng, Jiming Chen
    Abstract:

    Security of Cyber-Physical Systems (CPS) has gained increasing attention in recent years. Most existing works mainly investigate the system performance given some attacking patterns. In this technical note, we investigate how an attacker should schedule its Denial-of-Service (DoS) attacks to degrade the system performance. Specifically, we consider the scenario where a sensor sends its data to a remote estimator through a wireless channel, while an Energy-constrained attacker decides whether to jam the channel at each sampling time. We construct optimal attack schedules to maximize the expected average estimation error at the remote estimator. We also provide the optimal attack schedules when a special intrusion detection system (IDS) at the estimator is given. We further discuss the optimal attack schedules when the sensor has Energy Constraint. Numerical examples are presented to demonstrate the effectiveness of the proposed optimal attack schedules.

  • an online sensor power schedule for remote state estimation with communication Energy Constraint
    IEEE Transactions on Automatic Control, 2014
    Co-Authors: Peng Cheng, Jiming Chen
    Abstract:

    We consider sensor transmission power scheduling for remote state estimation with limited communication Energy. A sensor needs to decide when to switch between different transmission Energy levels in order to minimize the average expected estimation error covariance subject to the available Energy budget. In the existing work the sensor only exploits the prior knowledge of the system parameters, the noise covariance and the channel characteristics but neglects the realtime information the estimator can provide. Thanks to the power asymmetry between the sensor and the estimator, we propose an online scheduling scheme which makes a choice based on the acknowledgement sequence at the remote estimator side and show that the scheme outperforms the optimal offline schedule under the same Energy Constraint.

  • Optimal Periodic Sensor Schedule for Steady-State Estimation Under Average Transmission Energy Constraint
    IEEE Transactions on Automatic Control, 2013
    Co-Authors: Zhu Ren, Ling Shi, Peng Cheng, Jiming Chen, Youxian Sun
    Abstract:

    We consider periodic sensor scheduling for remote state estimation under average transmission Energy Constraint. The sensor decides whether or not to send its data to a remote estimator in order to meet the transmission Energy Constraint. The transmitted data are likely to be dropped due to the imperfect communication. An optimal periodic schedule is found via the tools from the Markov chain. Furthermore, a sufficient condition of the system dynamics, Energy budget, and packet drop rate, under which the remote estimator is guaranteed to be stable, is derived. Examples are provided to show the effectiveness of results.

  • Brief paper: Sensor data scheduling for optimal state estimation with communication Energy Constraint
    Automatica, 2011
    Co-Authors: Ling Shi, Peng Cheng, Jiming Chen
    Abstract:

    In this paper, we consider sensor data scheduling with communication Energy Constraint. A sensor has to decide whether to send its data to a remote estimator or not due to the limited available communication Energy. We construct effective sensor data scheduling schemes that minimize the estimation error and satisfy the Energy Constraint. Two scenarios are studied: the sensor has sufficient computation capability and the sensor has limited computation capability. For the first scenario, we are able to construct the optimal scheduling scheme. For the second scenario, we are able to provide lower and upper bounds of the minimum error and construct a scheduling scheme whose estimation error falls within the bounds.