支持泛洪攻击检测的命名数据网PIT

doi:10.13190/j.jbupt.2020-131

北京邮电大学学报 ›› 2021, Vol. 44 ›› Issue (2): 61-67.doi: 10.13190/j.jbupt.2020-131

• 未来网络体系架构和关键技术专题 • 上一篇下一篇

支持泛洪攻击检测的命名数据网PIT

彭鹏¹, 李卓¹, 梁纪峰², 马天祥², 刘开华¹

1. 天津大学微电子学院, 天津 300072;
2. 国网河北省电力有限公司电力科学研究院, 石家庄 050021

收稿日期:2020-08-20 出版日期:2021-04-28 发布日期:2021-04-28
通讯作者: 李卓(1984-),男,副教授,硕士生导师,E-mail:zli@tju.edu.cn. E-mail:zli@tju.edu.cn
作者简介:彭鹏(1995-),男,硕士生.
基金资助:
河北省省级科技计划项目（20314301D）；天津市科技计划项目（20JCQNJC01490）；国家自然科学基金项目（61602346）；天津大学自主创新基金项目（2020XRG-0102）

Research on Pending Interest Table of Named Data Networking Supporting Interest Flooding Attack Detection

PENG Peng¹, LI Zhuo¹, LIANG Ji-feng², MA Tian-xiang², LIU Kai-hua¹

1. School of Microelectronics, Tianjin University, Tianjin 300072, China;
2. Electric Power Research Institute, Hebei Electric Power Corporation, Shijiazhuang 050021, China

Received:2020-08-20 Online:2021-04-28 Published:2021-04-28

摘要/Abstract

摘要： 针对命名数据网待定兴趣转发表中高效的变长名称数据索引、硬件可支持的存储消耗以及兴趣包泛洪攻击检测等问题，提出了基于字符卷积神经网络的认知索引模型（C&I），该模型能够支持路由名称数据的分类、聚合，降低名称数据的存储消耗.同时，基于C&I提出了支持兴趣包泛洪攻击检测的待定兴趣转发表（PIT）存储结构C&I-PIT及其数据检索算法，通过多级存储器部署方式，分别在片上和片下的存储器中部署索引结构及存储空间.实验结果表明，C&I-PIT在名称数据聚合、存储消耗、泛洪攻击检测等方面具有良好的性能.

关键词: 命名数据网, 待定兴趣转发表, 名称数据索引, 字符卷积神经网络, 兴趣包泛洪攻击

Abstract: In order to solve the problems of efficient variable-length name lookup, hardware-supportable storage consumption, and detection of interest flooding attack in the pending interest table(PIT) of named data networking, an cognition and indexing model(C&I) based on character convolutional neural network is proposed. C&I can support the classification and aggregation of name data, and reduce the storage consumption of name data. At the same time, a pending interest table storage structure C&I-PIT based on C&I and its data retrieval algorithm, which supports the detection of interest flooding attack, is proposed. Through the deployment of multi-level memory, the index structure and storage space are respectively deployed on static random access memory and dynamic random access memory. Experiments show that C&I-PIT has good performance in name aggregation, memory consumption and interest flooding attack detection.

Key words: named data networking, pending interest table, name lookup, character convolutional neural network, interest flooding attack

中图分类号:

TP393

彭鹏, 李卓, 梁纪峰, 马天祥, 刘开华. 支持泛洪攻击检测的命名数据网PIT[J]. 北京邮电大学学报, 2021, 44(2): 61-67.

PENG Peng, LI Zhuo, LIANG Ji-feng, MA Tian-xiang, LIU Kai-hua. Research on Pending Interest Table of Named Data Networking Supporting Interest Flooding Attack Detection[J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(2): 61-67.

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支持泛洪攻击检测的命名数据网PIT

Research on Pending Interest Table of Named Data Networking Supporting Interest Flooding Attack Detection

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