The Experts below are selected from a list of 23895 Experts worldwide ranked by ideXlab platform
Osamu Muta - One of the best experts on this subject based on the ideXlab platform.
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a game theoretic approach for enhancing security and data trustworthiness in iot applications
IEEE Internet of Things Journal, 2020Co-Authors: Mohamed S Abdalzaher, Osamu MutaAbstract:Wireless sensor networks (WSNs)-based Internet of Things (IoT) are among the fast booming technologies that drastically contribute to different systems’ management and resilience data accessibility. Designing a robust IoT network imposes some challenges, such as data trustworthiness (DT) and power management. This article presents a repeated game model to enhance clustered WSNs-based IoT security and DT against the selective forwarding (SF) Attack. Besides, the model is capable of detecting the hardware (HW) failure of the cluster members (CMs), preserving the network stability, and conserving the power consumption due to packet retransmission. The model relies on the TDMA protocol to facilitate the detection process and to avoid collision between the delivered packets at the cluster head (CH). The proposed model aims to keep packets transmitting, isotropic or nonisotropic transmission, from the CMs to the CH for maximizing the DT and aims to distinguish between the Malicious CM and the one suffering from the HW failure. Accordingly, it can manage the consequently lost power due to the Malicious Attack effect or HW malfunction. The simulation results indicate the proposed mechanism improved performance with TDMA over six different environments against the SF Attack that achieves the Pareto-optimal DT as compared to a noncooperative defense mechanism.
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a game theoretic approach for enhancing security and data trustworthiness in iot applications
arXiv: Signal Processing, 2019Co-Authors: Mohamed S Abdalzaher, Osamu MutaAbstract:Wireless sensor networks (WSNs)-based internet of things (IoT) are among the fast booming technologies that drastically contribute to different systems management and resilience data accessibility. Designing a robust IoT network imposes some challenges such as data trustworthiness (DT) and power management. This paper presents a repeated game model to enhance clustered WSNs-based IoT security and DT against the selective forwarding (SF) Attack. Besides, the model is capable of detecting the hardware (HW) failure of the cluster members (CMs) and conserve the power consumption due to packet retransmission. The model relies on TDMA protocol to facilitate the detection process and to avoid collision between the delivered packets at the cluster head (CH). The proposed model aims to keep packets transmitting, isotropic or non-isotropic transmission, from the CMs to the CH for maximizing the DT and aims to distinguish between the Malicious CM and the one suffering from HW failure. Accordingly, it can manage the consequently lost power due to the Malicious Attack effect or HW malfunction. Simulation results indicate the proposed mechanism improved performance with TDMA over six different environments against the SF Attack that achieves the Pareto optimal DT as compared to a non-cooperative defense mechanism.
Mohamed S Abdalzaher - One of the best experts on this subject based on the ideXlab platform.
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a game theoretic approach for enhancing security and data trustworthiness in iot applications
IEEE Internet of Things Journal, 2020Co-Authors: Mohamed S Abdalzaher, Osamu MutaAbstract:Wireless sensor networks (WSNs)-based Internet of Things (IoT) are among the fast booming technologies that drastically contribute to different systems’ management and resilience data accessibility. Designing a robust IoT network imposes some challenges, such as data trustworthiness (DT) and power management. This article presents a repeated game model to enhance clustered WSNs-based IoT security and DT against the selective forwarding (SF) Attack. Besides, the model is capable of detecting the hardware (HW) failure of the cluster members (CMs), preserving the network stability, and conserving the power consumption due to packet retransmission. The model relies on the TDMA protocol to facilitate the detection process and to avoid collision between the delivered packets at the cluster head (CH). The proposed model aims to keep packets transmitting, isotropic or nonisotropic transmission, from the CMs to the CH for maximizing the DT and aims to distinguish between the Malicious CM and the one suffering from the HW failure. Accordingly, it can manage the consequently lost power due to the Malicious Attack effect or HW malfunction. The simulation results indicate the proposed mechanism improved performance with TDMA over six different environments against the SF Attack that achieves the Pareto-optimal DT as compared to a noncooperative defense mechanism.
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a game theoretic approach for enhancing security and data trustworthiness in iot applications
arXiv: Signal Processing, 2019Co-Authors: Mohamed S Abdalzaher, Osamu MutaAbstract:Wireless sensor networks (WSNs)-based internet of things (IoT) are among the fast booming technologies that drastically contribute to different systems management and resilience data accessibility. Designing a robust IoT network imposes some challenges such as data trustworthiness (DT) and power management. This paper presents a repeated game model to enhance clustered WSNs-based IoT security and DT against the selective forwarding (SF) Attack. Besides, the model is capable of detecting the hardware (HW) failure of the cluster members (CMs) and conserve the power consumption due to packet retransmission. The model relies on TDMA protocol to facilitate the detection process and to avoid collision between the delivered packets at the cluster head (CH). The proposed model aims to keep packets transmitting, isotropic or non-isotropic transmission, from the CMs to the CH for maximizing the DT and aims to distinguish between the Malicious CM and the one suffering from HW failure. Accordingly, it can manage the consequently lost power due to the Malicious Attack effect or HW malfunction. Simulation results indicate the proposed mechanism improved performance with TDMA over six different environments against the SF Attack that achieves the Pareto optimal DT as compared to a non-cooperative defense mechanism.
Ralph Gottschalg - One of the best experts on this subject based on the ideXlab platform.
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centralized volt var optimization strategy considering Malicious Attack on distributed energy resources control
Power and Energy Society General Meeting, 2018Co-Authors: Ankur Majumdar, Yashodhan Agalgoankar, Ralph GottschalgAbstract:The adoption of information and communication technology (ICT) based centralized volt-var control (VVC) leads to an optimal operation of a distribution feeder. However, it also poses a challenge that an adversary can tamper with the metered data and thus can render the VVC action ineffective. Distribution system state estimation (DSSE) acts as a backbone of centralized VVC. Distributed energy resources (DER) injection measurements constitute leverage measurements from a DSSE point of view. This paper proposes two solutions as a volt var optimization-distribution system state estimation (VVO-DSSE) Malicious Attack mitigating strategy when the DER injection measurements are compromised. The first solution is based on local voltage regulation controller set-points. The other solution effectively employs historical data or forecast information. The concept is based on a cumulant based probabilistic optimal power flow with the objective of minimizing the expectation of total power losses. The effectiveness of the approach is performed on the 95-bus UK generic distribution system (UKGDS) and validated against Monte Carlo simulations.
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centralized volt var optimization strategy considering Malicious Attack on distributed energy resources control
IEEE Transactions on Sustainable Energy, 2018Co-Authors: Ankur Majumdar, Yashodhan P Agalgaonkar, Ralph GottschalgAbstract:The adoption of information and communication technology based centralized volt–var control (VVC) leads to an optimal operation of a distribution feeder. However, it also poses a challenge that an adversary can tamper with the metered data and, thus, can render the VVC action ineffective. Distribution system state estimation (DSSE) acts as a backbone of centralized VVC. Distributed energy resources (DER) injection measurements constitute leverage measurements from a DSSE point of view. This paper proposes two solutions as a volt–var optimization DSSE Malicious Attack mitigating strategy when the DER injection measurements are compromised. The first solution is based on local voltage regulation controller set-points. The other solution effectively employs historical data or forecast information. The concept is based on a cumulant-based probabilistic optimal power flow with the objective of minimizing the expectation of total power losses. The effectiveness of the approach is performed on the 95-bus U.K. generic distribution system and validated against Monte Carlo simulations.
L I Ruijun - One of the best experts on this subject based on the ideXlab platform.
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semi fragile digital watermark algorithm based on image authentication
Computer Engineering, 2011Co-Authors: L I RuijunAbstract:A semi-fragile watermark algorithm for image authentication is proposed,which has adaptability,and uses improved low-pass filter.The threshold values of grads are set according to resolving power of human eyes.Experimental results show that the proposed algorithm is robust to common data processing,which can resist JEPG top-level compression,as well the algorithm is fragile to Malicious Attack,such as abrasion,distortion,extrusion,lighting,and so on.Moreover,the tampered sort and area of watermarked image can be reflected.
Ankur Majumdar - One of the best experts on this subject based on the ideXlab platform.
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centralized volt var optimization strategy considering Malicious Attack on distributed energy resources control
Power and Energy Society General Meeting, 2018Co-Authors: Ankur Majumdar, Yashodhan Agalgoankar, Ralph GottschalgAbstract:The adoption of information and communication technology (ICT) based centralized volt-var control (VVC) leads to an optimal operation of a distribution feeder. However, it also poses a challenge that an adversary can tamper with the metered data and thus can render the VVC action ineffective. Distribution system state estimation (DSSE) acts as a backbone of centralized VVC. Distributed energy resources (DER) injection measurements constitute leverage measurements from a DSSE point of view. This paper proposes two solutions as a volt var optimization-distribution system state estimation (VVO-DSSE) Malicious Attack mitigating strategy when the DER injection measurements are compromised. The first solution is based on local voltage regulation controller set-points. The other solution effectively employs historical data or forecast information. The concept is based on a cumulant based probabilistic optimal power flow with the objective of minimizing the expectation of total power losses. The effectiveness of the approach is performed on the 95-bus UK generic distribution system (UKGDS) and validated against Monte Carlo simulations.
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centralized volt var optimization strategy considering Malicious Attack on distributed energy resources control
IEEE Transactions on Sustainable Energy, 2018Co-Authors: Ankur Majumdar, Yashodhan P Agalgaonkar, Ralph GottschalgAbstract:The adoption of information and communication technology based centralized volt–var control (VVC) leads to an optimal operation of a distribution feeder. However, it also poses a challenge that an adversary can tamper with the metered data and, thus, can render the VVC action ineffective. Distribution system state estimation (DSSE) acts as a backbone of centralized VVC. Distributed energy resources (DER) injection measurements constitute leverage measurements from a DSSE point of view. This paper proposes two solutions as a volt–var optimization DSSE Malicious Attack mitigating strategy when the DER injection measurements are compromised. The first solution is based on local voltage regulation controller set-points. The other solution effectively employs historical data or forecast information. The concept is based on a cumulant-based probabilistic optimal power flow with the objective of minimizing the expectation of total power losses. The effectiveness of the approach is performed on the 95-bus U.K. generic distribution system and validated against Monte Carlo simulations.
