The Experts below are selected from a list of 309 Experts worldwide ranked by ideXlab platform

Laurence B. Milstein - One of the best experts on this subject based on the ideXlab platform.

  • CNS - Video cognitive radio networks for tactical scenarios
    2016 IEEE Conference on Communications and Network Security (CNS), 2016
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We examine the performance of uplink video transmission over a mobile cognitive radio (CR) system operating in a hostile environment where an Intelligent Adversary tries to disrupt communications. We investigate the optimal strategy for spoofing, desynchronizing and jamming a cluster-based CR network with a Gaussian noise signal, over a Rayleigh fading channel. The Adversary can limit access for secondary users (SUs) by either transmitting a spoofing signal in the sensing interval, or a desynchronizing signal to disrupt code acquisition by SUs or the cluster head. By jamming the network during the transmission interval, the Adversary can reduce the rate of successful transmission. We also propose cross-layer resource allocation algorithms and evaluate their performance under disruptive attacks.

  • Video cognitive radio networks for tactical scenarios
    2016 IEEE Conference on Communications and Network Security (CNS), 2016
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We examine the performance of uplink video transmission over a mobile cognitive radio (CR) system operating in a hostile environment where an Intelligent Adversary tries to disrupt communications. We investigate the optimal strategy for spoofing, desynchronizing and jamming a cluster-based CR network with a Gaussian noise signal, over a Rayleigh fading channel. The Adversary can limit access for secondary users (SUs) by either transmitting a spoofing signal in the sensing interval, or a desynchronizing signal to disrupt code acquisition by SUs or the cluster head. By jamming the network during the transmission interval, the Adversary can reduce the rate of successful transmission. We also propose cross-layer resource allocation algorithms and evaluate their performance under disruptive attacks.

  • Disruptive Attacks on Video Tactical Cognitive Radio Downlinks
    IEEE Transactions on Communications, 2016
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We consider video transmission over a mobile cognitive radio (CR) system operating in a hostile environment where an Intelligent Adversary tries to disrupt communications. We investigate the optimal strategy for spoofing, desynchronizing, and jamming a cluster-based CR network with a Gaussian noise signal over a slow Rayleigh fading channel. The Adversary can limit access for secondary users (SUs) by either transmitting a spoofing signal in the sensing interval, or a desynchronizing signal in the code acquisition interval. By jamming the network during the transmission interval, the Adversary can reduce the rate of successful transmission. We show how the Adversary can optimally allocate its energy across subcarriers during sensing, code acquisition, and transmission intervals. We determine a worst-case optimal energy allocation for spoofing, desynchronizing, and jamming, which gives an upper bound to the received video distortion of SUs. We also propose cross-layer resource allocation algorithms and evaluate their performance under disruptive attacks.

  • Optimized Spoofing and Jamming a Cognitive Radio
    IEEE Transactions on Communications, 2014
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We examine the performance of a cognitive radio system in a hostile environment where an Intelligent Adversary tries to disrupt communications by minimizing the system throughput. We investigate the optimal strategy for spoofing and jamming a cognitive radio network with a Gaussian noise signal over a Rayleigh fading channel. We analyze a cluster-based network of secondary users (SUs). The Adversary may attack during the sensing interval to limit access for SUs by transmitting a spoofing signal. By jamming the network during the transmission interval, the Adversary may reduce the rate of successful transmission. We present how the Adversary can optimally allocate power across subcarriers during sensing and transmission intervals with knowledge of the system, using a simple optimization approach specific to this problem. We determine a worst-case optimal energy allocation for spoofing and jamming, which gives a lower bound to the overall information throughput of SUs under attack.

  • GlobalSIP - Spoofing optimization over Nakagami-m fading channels of a cognitive radio Adversary
    2013 IEEE Global Conference on Signal and Information Processing, 2013
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We examine the performance of a cognitive radio system in a hostile environment where an Intelligent Adversary tries to disrupt communications by spoofing. We analyze a cluster-based network of secondary users (SUs), where sensing is performed by the cluster head. The Adversary may attack during the sensing interval to limit access for SUs by transmitting a Gaussian noise spoofing signal. We present how the Adversary can optimally allocate power across subcarriers during the sensing interval over Nakagami-m fading channels, using an optimization approach specific to this problem. We determine a worst-case optimal spoofing power allocation, when the Adversary has knowledge of the system, which gives a lower bound to the average number of accessible bands for SUs under attack.

Pamela C. Cosman - One of the best experts on this subject based on the ideXlab platform.

  • CNS - Video cognitive radio networks for tactical scenarios
    2016 IEEE Conference on Communications and Network Security (CNS), 2016
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We examine the performance of uplink video transmission over a mobile cognitive radio (CR) system operating in a hostile environment where an Intelligent Adversary tries to disrupt communications. We investigate the optimal strategy for spoofing, desynchronizing and jamming a cluster-based CR network with a Gaussian noise signal, over a Rayleigh fading channel. The Adversary can limit access for secondary users (SUs) by either transmitting a spoofing signal in the sensing interval, or a desynchronizing signal to disrupt code acquisition by SUs or the cluster head. By jamming the network during the transmission interval, the Adversary can reduce the rate of successful transmission. We also propose cross-layer resource allocation algorithms and evaluate their performance under disruptive attacks.

  • Video cognitive radio networks for tactical scenarios
    2016 IEEE Conference on Communications and Network Security (CNS), 2016
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We examine the performance of uplink video transmission over a mobile cognitive radio (CR) system operating in a hostile environment where an Intelligent Adversary tries to disrupt communications. We investigate the optimal strategy for spoofing, desynchronizing and jamming a cluster-based CR network with a Gaussian noise signal, over a Rayleigh fading channel. The Adversary can limit access for secondary users (SUs) by either transmitting a spoofing signal in the sensing interval, or a desynchronizing signal to disrupt code acquisition by SUs or the cluster head. By jamming the network during the transmission interval, the Adversary can reduce the rate of successful transmission. We also propose cross-layer resource allocation algorithms and evaluate their performance under disruptive attacks.

  • Disruptive Attacks on Video Tactical Cognitive Radio Downlinks
    IEEE Transactions on Communications, 2016
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We consider video transmission over a mobile cognitive radio (CR) system operating in a hostile environment where an Intelligent Adversary tries to disrupt communications. We investigate the optimal strategy for spoofing, desynchronizing, and jamming a cluster-based CR network with a Gaussian noise signal over a slow Rayleigh fading channel. The Adversary can limit access for secondary users (SUs) by either transmitting a spoofing signal in the sensing interval, or a desynchronizing signal in the code acquisition interval. By jamming the network during the transmission interval, the Adversary can reduce the rate of successful transmission. We show how the Adversary can optimally allocate its energy across subcarriers during sensing, code acquisition, and transmission intervals. We determine a worst-case optimal energy allocation for spoofing, desynchronizing, and jamming, which gives an upper bound to the received video distortion of SUs. We also propose cross-layer resource allocation algorithms and evaluate their performance under disruptive attacks.

  • Optimized Spoofing and Jamming a Cognitive Radio
    IEEE Transactions on Communications, 2014
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We examine the performance of a cognitive radio system in a hostile environment where an Intelligent Adversary tries to disrupt communications by minimizing the system throughput. We investigate the optimal strategy for spoofing and jamming a cognitive radio network with a Gaussian noise signal over a Rayleigh fading channel. We analyze a cluster-based network of secondary users (SUs). The Adversary may attack during the sensing interval to limit access for SUs by transmitting a spoofing signal. By jamming the network during the transmission interval, the Adversary may reduce the rate of successful transmission. We present how the Adversary can optimally allocate power across subcarriers during sensing and transmission intervals with knowledge of the system, using a simple optimization approach specific to this problem. We determine a worst-case optimal energy allocation for spoofing and jamming, which gives a lower bound to the overall information throughput of SUs under attack.

  • GlobalSIP - Spoofing optimization over Nakagami-m fading channels of a cognitive radio Adversary
    2013 IEEE Global Conference on Signal and Information Processing, 2013
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We examine the performance of a cognitive radio system in a hostile environment where an Intelligent Adversary tries to disrupt communications by spoofing. We analyze a cluster-based network of secondary users (SUs), where sensing is performed by the cluster head. The Adversary may attack during the sensing interval to limit access for SUs by transmitting a Gaussian noise spoofing signal. We present how the Adversary can optimally allocate power across subcarriers during the sensing interval over Nakagami-m fading channels, using an optimization approach specific to this problem. We determine a worst-case optimal spoofing power allocation, when the Adversary has knowledge of the system, which gives a lower bound to the average number of accessible bands for SUs under attack.

Gregory S. Parnell - One of the best experts on this subject based on the ideXlab platform.

  • a comparative analysis of pra and Intelligent Adversary methods for counterterrorism risk management
    Risk Analysis, 2011
    Co-Authors: Jason Merrick, Gregory S. Parnell
    Abstract:

    In counterterrorism risk management decisions, the analyst can choose to represent terrorist decisions as defender uncertainties or as attacker decisions. We perform a comparative analysis of probabilistic risk analysis (PRA) methods including event trees, influence diagrams, Bayesian networks, decision trees, game theory, and combined methods on the same illustrative examples (container screening for radiological materials) to get insights into the significant differences in assumptions and results. A key tenent of PRA and decision analysis is the use of subjective probability to assess the likelihood of possible outcomes. For each technique, we compare the assumptions, probability assessment requirements, risk levels, and potential insights for risk managers. We find that assessing the distribution of potential attacker decisions is a complex judgment task, particularly considering the adaptation of the attacker to defender decisions. Intelligent Adversary risk analysis and adversarial risk analysis are extensions of decision analysis and sequential game theory that help to decompose such judgments. These techniques explicitly show the adaptation of the attacker and the resulting shift in risk based on defender decisions. Language: en

  • A Comparative Analysis of PRA and Intelligent Adversary Methods for Counterterrorism Risk Management
    Risk Analysis, 2011
    Co-Authors: Jason Merrick, Gregory S. Parnell
    Abstract:

    In counterterrorism risk management decisions, the analyst can choose to represent terrorist decisions as defender uncertainties or as attacker decisions. We perform a comparative analysis of probabilistic risk analysis (PRA) methods including event trees, influence diagrams, Bayesian networks, decision trees, game theory, and combined methods on the same illustrative examples (container screening for radiological materials) to get insights into the significant differences in assumptions and results. A key tenent of PRA and decision analysis is the use of subjective probability to assess the likelihood of possible outcomes. For each technique, we compare the assumptions, probability assessment requirements, risk levels, and potential insights for risk managers. We find that assessing the distribution of potential attacker decisions is a complex judgment task, particularly considering the adaptation of the attacker to defender decisions. Intelligent Adversary risk analysis and adversarial risk analysis are extensions of decision analysis and sequential game theory that help to decompose such judgments. These techniques explicitly show the adaptation of the attacker and the resulting shift in risk based on defender decisions.

  • Intelligent Adversary risk analysis a bioterrorism risk management model
    Risk Analysis, 2010
    Co-Authors: Gregory S. Parnell, Christopher M Smith, Frederick I Moxley
    Abstract:

    The tragic events of 9/11 and the concerns about the potential for a terrorist or hostile state attack with weapons of mass destruction have led to an increased emphasis on risk analysis for homeland security. Uncertain hazards (natural and engineering) have been successfully analyzed using probabilistic risk analysis (PRA). Unlike uncertain hazards, terrorists and hostile states are Intelligent adversaries who can observe our vulnerabilities and dynamically adapt their plans and actions to achieve their objectives. This article compares uncertain hazard risk analysis with Intelligent Adversary risk analysis, describes the Intelligent Adversary risk analysis challenges, and presents a probabilistic defender-attacker-defender model to evaluate the baseline risk and the potential risk reduction provided by defender investments. The model includes defender decisions prior to an attack; attacker decisions during the attack; defender actions after an attack; and the uncertainties of attack implementation, detection, and consequences. The risk management model is demonstrated with an illustrative bioterrorism problem with notional data. Language: en

  • Intelligent Adversary risk analysis a bioterrorism risk management model preprint
    2009
    Co-Authors: Gregory S. Parnell, Christopher M Smith, Frederick I Moxley
    Abstract:

    Abstract : The tragic events of 911 and the concerns about the potential for a terrorist or hostile state attack with weapons of mass destruction have led to an increased emphasis on risk analysis for homeland security. Uncertain hazards (natural and engineering) have been analyzed using Probabilistic Risk Analysis (PRA). Unlike uncertain hazards, terrorists and hostile states are Intelligent adversaries who adapt their plans and actions to achieve their strategic objectives. The critical risk analysis question addressed in this paper is as follows: Are the standard PRA techniques for uncertain hazard techniques adequate and appropriate for Intelligent adversaries? Our answer is an emphatic no. We will show that treating Adversary decisions as uncertain hazards is inappropriate because it provides the wrong assessment of risks. Specifically, the paper compares uncertain hazard risk analysis with Intelligent Adversary risk analysis, describes the Intelligent Adversary risk analysis challenges, and uses a defender-attacker-defender decision analysis model to evaluate defender investments. The model includes defender decisions prior to an attack; attacker decisions during the attack; defender actions after an attack; and the uncertainties of attack implementation, detection, and consequences. In section 1, we describe the difference between natural hazards and Intelligent adversaries and demonstrate, with a simple example, that standard PRA does not properly assess the risk of an Intelligent Adversary attack. In section 2, we describe a canonical model for resource allocation decision making for an Intelligent Adversary problem using an illustrative bioterrorism example with notional data. In section 3, we describe the illustrative analysis results obtained for the model and discuss the insights they provide for risk management. In section 4, we describe the benefits and limitations of the model. Finally, we discuss future work and our conclusions.

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

  • Optimal sensing-deception strategy with fading in cognitive radio networks
    2012 International Conference on Computational Problem-Solving (ICCP), 2012
    Co-Authors: Qihang Peng, Pamela C. Cosman, Dingyong Hu, Qicong Peng, Laurence B. Milstein
    Abstract:

    The optimal sensing-deception strategy by a power-limited Intelligent Adversary of a cognitive radio network is analyzed in this paper. The average number of false detections of the secondary users is maximized when the Adversary employs noise spoofing signals, and each such signal experiences multipath-induced fading. The global optimal solution to what turns out to be a nonlinear, non-convex optimization is obtained through a two-step transformation. Numerical results show that, under i.i.d. Rayleigh fading, the optimal sensing-deception strategy for the Adversary corresponds to equal-power, partial-band spoofing.

  • Spoofing or Jamming: Performance Analysis of a Tactical Cognitive Radio Adversary
    IEEE Journal on Selected Areas in Communications, 2011
    Co-Authors: Qihang Peng, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    The tradeoff between spoofing and jamming a cognitive radio network by an Intelligent Adversary is analyzed in this paper. Due to the vulnerabilities of spectrum sensing noted in recent studies, a cognitive radio can be attacked during the sensing interval by an Adversary who puts spoofing signals in unused bands. Further, once secondary users access unused bands, the Adversary can use traditional jamming to interfere with them during transmission. For an energy-constrained Intelligent Adversary, a two step procedure is formulated to distribute the energy between spoofing and jamming, such that the average sum throughput of the secondary users is minimized. That is, we optimally spoof in the sensing duration and then optimally jam in the transmission slot. In a cluster-based cognitive radio network, when the number of spectral vacancies required by secondary users increases, the optimal attack for the Intelligent Adversary will shift from jamming only, to a combination of spoofing and jamming, to spoofing only.

  • Optimal Sensing Disruption for a Cognitive Radio Adversary
    IEEE Transactions on Vehicular Technology, 2010
    Co-Authors: Qihang Peng, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    Spectrum sensing vulnerabilities in cognitive radio (CR) networks are being actively investigated, where most research focuses on mechanisms that deal with possible attacks without examining optimal sensing disruption strategies. This paper addresses the optimal design and analysis of a power-limited Intelligent Adversary to a CR network. The Adversary targets unused bands and puts energy into them so that the number of unused bands appears reduced to secondary users. This is called sensing disruption. The optimal disruption strategy is obtained by maximizing the average number of false detections under the Adversary's power constraint. It is shown that, for a CR network where energy detection is utilized by secondary users, the optimal sensing disruption strategy for noise spoofing for a CR Adversary is equal-power partial-band spoofing. Numerical results and analyses of the optimal sensing disruption are provided.

  • Analysis and Simulation of Sensing Deception in Fading Cognitive Radio Networks
    2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM), 2010
    Co-Authors: Qihang Peng, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We are interested in determining the sensitivity of a tactical cognitive radio (CR) system to intentional spoofing. That is, we assume the existence of an Intelligent Adversary whose goal is to attack the CR system by deceiving the secondary users into believing that as many frequency bands as possible are occupied by primary users, thus minimizing the number of bands in which the secondary users attempt to transmit. We refer to this operation by the Adversary as "spoofing", and the specific spoofing signal we choose is a partial-band noise waveform. That is, for a given total power level that is available to the Adversary, we maximize the average number of false detections incurred by secondary users as a result of the spoofing. We consider a channel such that each band experiences flat Rayleigh fading, whereby the fading is independent from band to band, and derive the average number of false detections by the secondary users due to the spoofing. The results obtained for the fading channel are compared to similar results for an additive white Gaussian noise channel (AWGN). They are also compared to a physically unrealizable scenario whereby the spoofing knows the instantaneous fade gains of the spoofing waveform at the victim CR receiver. This latter result is presented as a "worst-case" perspective as to how well the spoofing operation can be expected to perform.

  • Tradeoff between spoofing and jamming a cognitive radio
    2009 Conference Record of the Forty-Third Asilomar Conference on Signals Systems and Computers, 2009
    Co-Authors: Qihang Peng, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    Recent studies show that spectrum sensing in cognitive radio exposes vulnerabilities to adversaries. An Intelligent Adversary can launch sensing disruption in the sensing duration, by putting spoofing signals in allowable bands to prevent secondary users from accessing. In the meantime, the Adversary can also attack secondary users by traditional jamming, once they access the spectral bands and start transmission. Both attacks can significantly degrade the performance of a cognitive radio system. In this paper, we address the design of an energy constrained Intelligent Adversary. More specifically, a global optimization problem is formulated, to optimally distribute its energy between spoofing and jamming, so that the average sum throughput of the secondary users is minimized. To simplify the computation complexities, we divide our optimization into a 2-step problem: first optimally spoof and then optimally jam. Numerical results show that, to induce the worst effect on the average sum throughput of the secondary users, there is a tradeoff between spoofing and jamming: 1) when spoofing and jamming capabilities are comparable, the optimal attack is a combination of partial-band spoofing and partial-band jamming; 2) when spoofing is more effective, a spoofing only strategy is required; 3) when jamming capability dominates, a jamming only attack should be adopted.

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

  • CNS - Video cognitive radio networks for tactical scenarios
    2016 IEEE Conference on Communications and Network Security (CNS), 2016
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We examine the performance of uplink video transmission over a mobile cognitive radio (CR) system operating in a hostile environment where an Intelligent Adversary tries to disrupt communications. We investigate the optimal strategy for spoofing, desynchronizing and jamming a cluster-based CR network with a Gaussian noise signal, over a Rayleigh fading channel. The Adversary can limit access for secondary users (SUs) by either transmitting a spoofing signal in the sensing interval, or a desynchronizing signal to disrupt code acquisition by SUs or the cluster head. By jamming the network during the transmission interval, the Adversary can reduce the rate of successful transmission. We also propose cross-layer resource allocation algorithms and evaluate their performance under disruptive attacks.

  • Video cognitive radio networks for tactical scenarios
    2016 IEEE Conference on Communications and Network Security (CNS), 2016
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We examine the performance of uplink video transmission over a mobile cognitive radio (CR) system operating in a hostile environment where an Intelligent Adversary tries to disrupt communications. We investigate the optimal strategy for spoofing, desynchronizing and jamming a cluster-based CR network with a Gaussian noise signal, over a Rayleigh fading channel. The Adversary can limit access for secondary users (SUs) by either transmitting a spoofing signal in the sensing interval, or a desynchronizing signal to disrupt code acquisition by SUs or the cluster head. By jamming the network during the transmission interval, the Adversary can reduce the rate of successful transmission. We also propose cross-layer resource allocation algorithms and evaluate their performance under disruptive attacks.

  • Disruptive Attacks on Video Tactical Cognitive Radio Downlinks
    IEEE Transactions on Communications, 2016
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We consider video transmission over a mobile cognitive radio (CR) system operating in a hostile environment where an Intelligent Adversary tries to disrupt communications. We investigate the optimal strategy for spoofing, desynchronizing, and jamming a cluster-based CR network with a Gaussian noise signal over a slow Rayleigh fading channel. The Adversary can limit access for secondary users (SUs) by either transmitting a spoofing signal in the sensing interval, or a desynchronizing signal in the code acquisition interval. By jamming the network during the transmission interval, the Adversary can reduce the rate of successful transmission. We show how the Adversary can optimally allocate its energy across subcarriers during sensing, code acquisition, and transmission intervals. We determine a worst-case optimal energy allocation for spoofing, desynchronizing, and jamming, which gives an upper bound to the received video distortion of SUs. We also propose cross-layer resource allocation algorithms and evaluate their performance under disruptive attacks.

  • Optimized Spoofing and Jamming a Cognitive Radio
    IEEE Transactions on Communications, 2014
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We examine the performance of a cognitive radio system in a hostile environment where an Intelligent Adversary tries to disrupt communications by minimizing the system throughput. We investigate the optimal strategy for spoofing and jamming a cognitive radio network with a Gaussian noise signal over a Rayleigh fading channel. We analyze a cluster-based network of secondary users (SUs). The Adversary may attack during the sensing interval to limit access for SUs by transmitting a spoofing signal. By jamming the network during the transmission interval, the Adversary may reduce the rate of successful transmission. We present how the Adversary can optimally allocate power across subcarriers during sensing and transmission intervals with knowledge of the system, using a simple optimization approach specific to this problem. We determine a worst-case optimal energy allocation for spoofing and jamming, which gives a lower bound to the overall information throughput of SUs under attack.

  • GlobalSIP - Spoofing optimization over Nakagami-m fading channels of a cognitive radio Adversary
    2013 IEEE Global Conference on Signal and Information Processing, 2013
    Co-Authors: Madushanka Soysa, Pamela C. Cosman, Laurence B. Milstein
    Abstract:

    We examine the performance of a cognitive radio system in a hostile environment where an Intelligent Adversary tries to disrupt communications by spoofing. We analyze a cluster-based network of secondary users (SUs), where sensing is performed by the cluster head. The Adversary may attack during the sensing interval to limit access for SUs by transmitting a Gaussian noise spoofing signal. We present how the Adversary can optimally allocate power across subcarriers during the sensing interval over Nakagami-m fading channels, using an optimization approach specific to this problem. We determine a worst-case optimal spoofing power allocation, when the Adversary has knowledge of the system, which gives a lower bound to the average number of accessible bands for SUs under attack.