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Shen, Qili, Wu, Jun, Li, Jianhua.  2019.  Edge Learning Based Green Content Distribution for Information-Centric Internet of Things. 2019 42nd International Conference on Telecommunications and Signal Processing (TSP). :67–70.
Being the revolutionary future networking architecture, information-centric networking (ICN) conducts network distribution based on content, which is ideally suitable for Internet of things (IoT). With the rapid growth of network traffic, compared to the conventional IoT, information-centric Internet of things (IC-IoT) is expected to provide users with the better satisfaction of the network quality of service (QoS). However, due to IC-IoT requirements of low latency, large data volume, marginalization, and intelligent processing, it urgently needs an efficient content distribution system. In this paper, we propose an edge learning based green content distribution scheme for IC-IoT. We implement intelligent path selection based on decision tree and edge calculation. Moreover, we apply distributed coding based content transmission to enhance the speed and recovery capability of content. Meanwhile, we have verified the effectiveness and performance of this scheme based on a large number of simulation experiments. The work of this paper is of great significance to improve the efficiency and flexibility of content distribution in IC-IoT.
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Liu, Yi, Dong, Mianxiong, Ota, Kaoru, Wu, Jun, Li, Jianhua, Chen, Hao.  2019.  SCTD: Smart Reasoning Based Content Threat Defense in Semantics Knowledge Enhanced ICN. ICC 2019 - 2019 IEEE International Conference on Communications (ICC). :1–6.
Information-centric networking (ICN) is a novel networking architecture with subscription-based naming mechanism and efficient caching, which has abundant semantic features. However, existing defense studies in ICN fails to isolate or block efficiently novel content threats including malicious penetration and semantic obfuscation for the lack of researches considering ICN semantic features. More importantly, to detect potential threats, existing security works in ICN fail to use semantic reasoning to construct security knowledge-based defense mechanism. Thus ICN needs a smart and content-based defense mechanism. Current works are not able to block content threats implicated in semantics. Additionally, based on traditional computing resources, they are incompatible with ICN protocols. In this paper, we propose smart reasoning based content threat defense for semantics knowledge enhanced ICN. A fog computing based defense mechanism with content semantic awareness is designed to build ICN edge defense system. In addition, smart reasoning algorithms is proposed to detect implicit knowledge and semantic relations in packet names and contents with context communication content and knowledge graph. On top of inference knowledge, the mechanism can perceive threats from ICN interests. Simulations demonstrate the validity and efficiency of the proposed mechanism.
Lin, Gengshen, Dong, Mianxiong, Ota, Kaoru, Li, Jianhua, Yang, Wu, Wu, Jun.  2019.  Security Function Virtualization Based Moving Target Defense of SDN-Enabled Smart Grid. ICC 2019 - 2019 IEEE International Conference on Communications (ICC). :1–6.

Software-defined networking (SDN) allows the smart grid to be centrally controlled and managed by decoupling the control plane from the data plane, but it also expands attack surface for attackers. Existing studies about the security of SDN-enabled smart grid (SDSG) mainly focused on static methods such as access control and identity authentication, which is vulnerable to attackers that carefully probe the system. As the attacks become more variable and complex, there is an urgent need for dynamic defense methods. In this paper, we propose a security function virtualization (SFV) based moving target defense of SDSG which makes the attack surface constantly changing. First, we design a dynamic defense mechanism by migrating virtual security function (VSF) instances as the traffic state changes. The centralized SDN controller is re-designed for global status monitoring and migration management. Moreover, we formalize the VSF instances migration problem as an integer nonlinear programming problem with multiple constraints and design a pre-migration algorithm to prevent VSF instances' resources from being exhausted. Simulation results indicate the feasibility of the proposed scheme.

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Cui, Liqun, Dong, Mianxiong, Ota, Kaoru, Wu, Jun, Li, Jianhua, Wu, Yang.  2019.  NSTN: Name-Based Smart Tracking for Network Status in Information-Centric Internet of Things. ICC 2019 - 2019 IEEE International Conference on Communications (ICC). :1–6.
Internet of Things(IoT) is an important part of the new generation of information technology and an important stage of development in the era of informatization. As a next generation network, Information Centric Network (ICN) has been introduced into the IoT, leading to the content independence of IC-IoT. To manage the changing network conditions and diagnose the cause of anomalies within it, network operators must obtain and analyze network status information from monitoring tools. However, traditional network supervision method will not be applicable to IC-IoT centered on content rather than IP. Moreover, the surge in information volume will also bring about insufficient information distribution, and the data location in the traditional management information base is fixed and cannot be added or deleted. To overcome these problems, we propose a name-based smart tracking system to store network state information in the IC-IoT. Firstly, we design a new structure of management information base that records various network state information and changes its naming format. Secondly, we use a tracking method to obtain the required network status information. When the manager issues a status request, each data block has a defined data tracking table to record past requests, the location of the status data required can be located according to it. Thirdly, we put forward an adaptive network data location replacement strategy based on the importance of stored data blocks, so that the information with higher importance will be closer to the management center for more efficient acquisition. Simulation results indicate the feasibility of the proposed scheme.