Yufu Wang, Yuan Liu, Jinzong Hu, Mingwei Zhang, Xingwei Wang
{"title":"Reputation and Incentive Mechanism for SDN Applications","authors":"Yufu Wang, Yuan Liu, Jinzong Hu, Mingwei Zhang, Xingwei Wang","doi":"10.1109/MSN.2018.000-3","DOIUrl":null,"url":null,"abstract":"Software Defined Networking (SDN) decouples the control plane from the data plane, which increases network scalability and flexibility. But malicious applications on SDN controller can cause the entire network to crash. So, we design a reputation and incentive mechanism on SDN to reduce application's malicious access. In the proposed module, first of all, the application behavior is analyzed and the malicious accesses are identified, which are used to build the reputation and incentive mechanism. Second, the analysis results of the application behavior are combined through beta probability density to obtain the reputation rating. The reward or punishment will be given based on the behavior and reputation of the application under the selected social strategy. Simulation results show that the system can accurately identify malicious behavior and reduce malicious requests, with an acceptable runtime overhead about 300 microseconds.","PeriodicalId":264541,"journal":{"name":"2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MSN.2018.000-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Software Defined Networking (SDN) decouples the control plane from the data plane, which increases network scalability and flexibility. But malicious applications on SDN controller can cause the entire network to crash. So, we design a reputation and incentive mechanism on SDN to reduce application's malicious access. In the proposed module, first of all, the application behavior is analyzed and the malicious accesses are identified, which are used to build the reputation and incentive mechanism. Second, the analysis results of the application behavior are combined through beta probability density to obtain the reputation rating. The reward or punishment will be given based on the behavior and reputation of the application under the selected social strategy. Simulation results show that the system can accurately identify malicious behavior and reduce malicious requests, with an acceptable runtime overhead about 300 microseconds.
SDN (Software Defined Networking)将控制平面和数据平面解耦,提高了网络的可扩展性和灵活性。但是SDN控制器上的恶意应用程序会导致整个网络崩溃。为此,我们在SDN网络上设计了信誉和激励机制,以减少应用程序的恶意访问。在该模块中,首先对应用行为进行分析,识别恶意访问,并据此建立信誉和激励机制。其次,通过β概率密度对应用行为的分析结果进行组合,得到信誉评级;在选定的社会策略下,将根据应用程序的行为和声誉给予奖励或惩罚。仿真结果表明,该系统能够准确识别恶意行为,减少恶意请求,运行时开销约为300微秒。