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

被引：0
|
作者：
Peng P. [1 ]
Li Z. [1 ]
Liang J.-F. [2 ]
Ma T.-X. [2 ]
Liu K.-H. [1 ]
机构：
[1] School of Microelectronics, Tianjin University, Tianjin
[2] Electric Power Research Institute, Hebei Electric Power Corporation, Shijiazhuang
来源：
Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications | 2021年 / 44卷 / 02期
关键词：
Character convolutional neural network; Interest flooding attack; Name lookup; Named data networking; Pending interest table;
D O I：
10.13190/j.jbupt.2020-131
中图分类号：
学科分类号：
摘要：
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. © 2021, Editorial Department of Journal of Beijing University of Posts and Telecommunications. All right reserved.
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页码：61 / 67
页数：6
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