新型命名数据网络校验机制设计

发布时间：2018-04-22 20:01

  本文选题：命名数据网络 + 内容污染　； 参考：《北京邮电大学学报》2017年03期

【摘要】：提出了一种基于流行度的概率存入校验机制(PCS-CP),根据接收内容的流行度,概率抽取内容校验,并只存入校验通过内容,确保节点的有限计算资源尽可能服务于用户关注内容,无须校验网内命中内容,降低了校验开销.由于PCS-CP机制只有与特定缓存策略配合才能最大化效用,进而提出了一种基于缓存更新时间的网内缓存策略,对网内副本冗余进行优化控制,有效提升了PCS-CP机制的校验效果.数值结果表明,与命中校验机制相比,PCS-CP可有效降低网内校验次数,有效防御内容污染攻击.
[Abstract]:In this paper, a probabilistic checkout mechanism based on popularity is proposed. According to the popularity of the received content, the probabilistic content is extracted and checked, and only the content is stored, so as to ensure that the limited computing resources of the node serve the user's attention as much as possible. There is no need to check the content of the hit in the network, reducing the cost of verification. Since the PCS-CP mechanism can only maximize the effectiveness with a specific cache policy, this paper proposes a cache policy based on cache update time, which optimizes the redundancy of replicas in the network and effectively improves the verification effect of the PCS-CP mechanism. The numerical results show that PCS-CP can effectively reduce the number of checks in the network and effectively defend against the attack of content pollution compared with the hit check mechanism.
【作者单位】： 江苏大学计算机科学与通信工程学院;
【基金】：国家自然科学基金项目(41474095)
【分类号】：TP393.08
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本文编号：1788704