The Experts below are selected from a list of 36 Experts worldwide ranked by ideXlab platform
Wenwu Zhu - One of the best experts on this subject based on the ideXlab platform.
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ICDCS - Localized Low-Power Topology Control Algorithms in IEEE 802.15.4-Based Sensor Networks
25th IEEE International Conference on Distributed Computing Systems (ICDCS'05), 1Co-Authors: Min Gao, Qian Zhang, Wenwu ZhuAbstract:Sensor networks have emerged as a promising technology with various applications, and power consumption is one of the key issues. Since each full function device can act as a coordinator or a device in IEEE 802.15.4 standard, 802.15.4-based sensor networks have various possible network topologies. In this paper, we try to construct network topologies with small number of coordinators while still maintaining network connectivity. By reducing the number of coordinators, the average duty cycle is reduced and the battery life is prolonged. Three topology control algorithms are proposed in this paper. Self-pruning is the simplest one with O(l) running time. Ordinal pruning significantly improves self-pruning in terms of power saving with O(n) running time. Layered pruning is a tradeoff between the first two pruning algorithms with O(radicn) running time and a little higher power consumption than ordinal pruning. Furthermore, all three algorithms are independent of the physical radio propagation characteristics
Min Gao - One of the best experts on this subject based on the ideXlab platform.
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ICDCS - Localized Low-Power Topology Control Algorithms in IEEE 802.15.4-Based Sensor Networks
25th IEEE International Conference on Distributed Computing Systems (ICDCS'05), 1Co-Authors: Min Gao, Qian Zhang, Wenwu ZhuAbstract:Sensor networks have emerged as a promising technology with various applications, and power consumption is one of the key issues. Since each full function device can act as a coordinator or a device in IEEE 802.15.4 standard, 802.15.4-based sensor networks have various possible network topologies. In this paper, we try to construct network topologies with small number of coordinators while still maintaining network connectivity. By reducing the number of coordinators, the average duty cycle is reduced and the battery life is prolonged. Three topology control algorithms are proposed in this paper. Self-pruning is the simplest one with O(l) running time. Ordinal pruning significantly improves self-pruning in terms of power saving with O(n) running time. Layered pruning is a tradeoff between the first two pruning algorithms with O(radicn) running time and a little higher power consumption than ordinal pruning. Furthermore, all three algorithms are independent of the physical radio propagation characteristics
Qian Zhang - One of the best experts on this subject based on the ideXlab platform.
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ICDCS - Localized Low-Power Topology Control Algorithms in IEEE 802.15.4-Based Sensor Networks
25th IEEE International Conference on Distributed Computing Systems (ICDCS'05), 1Co-Authors: Min Gao, Qian Zhang, Wenwu ZhuAbstract:Sensor networks have emerged as a promising technology with various applications, and power consumption is one of the key issues. Since each full function device can act as a coordinator or a device in IEEE 802.15.4 standard, 802.15.4-based sensor networks have various possible network topologies. In this paper, we try to construct network topologies with small number of coordinators while still maintaining network connectivity. By reducing the number of coordinators, the average duty cycle is reduced and the battery life is prolonged. Three topology control algorithms are proposed in this paper. Self-pruning is the simplest one with O(l) running time. Ordinal pruning significantly improves self-pruning in terms of power saving with O(n) running time. Layered pruning is a tradeoff between the first two pruning algorithms with O(radicn) running time and a little higher power consumption than ordinal pruning. Furthermore, all three algorithms are independent of the physical radio propagation characteristics
Weiming Shen - One of the best experts on this subject based on the ideXlab platform.
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A Collaborative PHY-Aided Technique for End-to-End IoT device Authentication
IEEE Access, 2018Co-Authors: Peng Hao, Xianbin Wang, Weiming ShenAbstract:Nowadays, Internet of Things (IoT) devices are rapidly proliferating to support a vast number of end-to-end (E2E) services and applications, which require reliable device authentication for E2E data security. However, most low-cost IoT end devices with limited computing resources have difficulties in executing the increasingly complicated cryptographic security protocols, resulting in increased vulnerability of the virtual authentication credentials to malicious cryptanalysis. An attacker possessing compromised credentials could be deemed legitimate by the conventional cryptography-based authentication. Although inherently robust to upper-layer unauthorized cryptanalysis, the device-to-device physical-layer (PHY) authentication is practically difficult to be applied to the E2E IoT scenario and to be integrated with the existing, well-established cryptography primitives without any conflict. This paper proposes an enhanced E2E IoT device authentication that achieves seamless integration of PHY security into traditional asymmetric cryptography-based authentication schemes. Exploiting the collaboration of several intermediate nodes (e.g., edge gateway, access point, and full-function device), multiple radio-frequency features of an IoT device can be estimated, quantized, and used in the proposed PHY identity-based cryptography for key protection. A closed-form expression of the generated PHY entropy is derived for measuring the security enhancement. The evaluation results of our cross-layer authentication demonstrate an elevated resistance to various computation-based impersonation attacks. Furthermore, the proposed method does not impose any extra implementation overhead on resource-constrained IoT devices.
Peng Hao - One of the best experts on this subject based on the ideXlab platform.
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A Collaborative PHY-Aided Technique for End-to-End IoT device Authentication
IEEE Access, 2018Co-Authors: Peng Hao, Xianbin Wang, Weiming ShenAbstract:Nowadays, Internet of Things (IoT) devices are rapidly proliferating to support a vast number of end-to-end (E2E) services and applications, which require reliable device authentication for E2E data security. However, most low-cost IoT end devices with limited computing resources have difficulties in executing the increasingly complicated cryptographic security protocols, resulting in increased vulnerability of the virtual authentication credentials to malicious cryptanalysis. An attacker possessing compromised credentials could be deemed legitimate by the conventional cryptography-based authentication. Although inherently robust to upper-layer unauthorized cryptanalysis, the device-to-device physical-layer (PHY) authentication is practically difficult to be applied to the E2E IoT scenario and to be integrated with the existing, well-established cryptography primitives without any conflict. This paper proposes an enhanced E2E IoT device authentication that achieves seamless integration of PHY security into traditional asymmetric cryptography-based authentication schemes. Exploiting the collaboration of several intermediate nodes (e.g., edge gateway, access point, and full-function device), multiple radio-frequency features of an IoT device can be estimated, quantized, and used in the proposed PHY identity-based cryptography for key protection. A closed-form expression of the generated PHY entropy is derived for measuring the security enhancement. The evaluation results of our cross-layer authentication demonstrate an elevated resistance to various computation-based impersonation attacks. Furthermore, the proposed method does not impose any extra implementation overhead on resource-constrained IoT devices.
