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A General SDN-Based IoT Framework with NVF Implementation
Jie Li, Eitan Altman, Corinne Touati
ZTE Communications 2015, 13 (
3
): 42-45. DOI:
10.3969/j.issn.1673-5188.2015.03.006
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309
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The emerging technologies of Internet of Things (IoT), software defined networking (SDN), and network function virtualization (NFV) have great potential for the information service innovation in the cloud and big data era. The architecture models of IoT, SDN with NFV implementation are studied in this paper. A general SDN-based IoT framework with NFV implantation is presented. This framework takes advantages of SDN and NFV and improves IoT architecture.
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An Instance-Learning-Based Intrusion-Detection System forWireless Sensor Networks
Shuai Fu, Xiaoyan Wang, Jie Li
ZTE Communications 2015, 13 (
2
): 7-11. DOI:
10.3969/j.issn.1673-5188.2015.02.002
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112
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This paper proposes an instance-learning-based intrusion-detection system (IL-IDS) for wireless sensor networks (WSNs). The goal of the proposed system is to detect routing attacks on a WSN. Taking an existing instance-learning algorithm for wired networks as our basis, we propose IL-IDS for handling routing security problems in a WSN. Attacks on a routing protocol for a WSN include black hole attack and sinkhole attack. The basic idea of our system is to differentiate the changes between secure instances and attack instances. Considering the limited resources of sensor nodes, the existing algorithm cannot be used directly in a WSN. Our system mainly comprises four parts: feature vector selection, threshold selection, instance data processing, and instance determination. We create a feature vector form composed of the attributes that changes obviously when an attack occurs within the network. For the data processing in resource-constrained sensor nodes, we propose a data-reduction scheme based on the clustering algorithm. For instance determination, we provide a threshold-selection scheme and describe the concrete-instance-determination mechanism of the system. Finally, we simulate and evaluate the proposed IL-IDS for different types of attacks.
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Data Security and Privacy in Cloud Storage
Xinhua Dong, Ruixuan Li, Wanwan Zhou, Dongjie Liao, and Shuoyi Zhao
ZTE Communications 2013, 11 (
2
): 18-23. DOI:
DOI:10.3969/j.issn.1673-5188.2013.02.003
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83
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In this paper, we survey data security and privacy problems created by cloud storage applications and propose a cloud storage security architecture. We discuss state-of-the-art techniques for ensuring the privacy and security of data stored in the cloud. We discuss policies for access control and data integrity, availability, and privacy. We also discuss several key solutions proposed in current literature and point out future research directions.
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