Internet of Things Intrusion Detection System Based on Convolutional Neural Network

被引:5
|
作者
Yin, Jie [1 ,2 ,3 ]
Shi, Yuxuan [1 ]
Deng, Wen [1 ]
Yin, Chang [1 ]
Wang, Tiannan [1 ]
Song, Yuchen [1 ]
Li, Tianyao [1 ]
Li, Yicheng [1 ]
机构
[1] Jiangsu Police Inst, Dept Comp Informat & Cyber Secur, Nanjing, Peoples R China
[2] Engn Res Ctr Elect Data Forens Anal, Nanjing, Peoples R China
[3] Dept Publ Secur Jiangsu Prov, Key Lab Digital Forens, Nanjing, Peoples R China
来源
CMC-COMPUTERS MATERIALS & CONTINUA | 2023年 / 75卷 / 01期
关键词
Internet of things; intrusion detection system; convolutional neural network; federated learning; DEEP LEARNING APPROACH;
D O I
10.32604/cmc.2023.035077
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, the Internet of Things (IoT) technology has devel-oped by leaps and bounds. However, the large and heterogeneous network structure of IoT brings high management costs. In particular, the low cost of IoT devices exposes them to more serious security concerns. First, a convolutional neural network intrusion detection system for IoT devices is proposed. After cleaning and preprocessing the NSL-KDD dataset, this paper uses feature engineering methods to select appropriate features. Then, based on the combination of DCNN and machine learning, this paper designs a cloud-based loss function, which adopts a regularization method to prevent overfitting. The model consists of one input layer, two convolutional layers, two pooling layers and three fully connected layers and one output layer. Finally, a framework that can fully consider the user's privacy protection is proposed. The framework can only exchange model parameters or interme-diate results without exchanging local individuals or sample data. This paper further builds a global model based on virtual fusion data, so as to achieve a balance between data privacy protection and data sharing computing. The performance indicators such as accuracy, precision, recall, F1 score, and AUC of the model are verified by simulation. The results show that the model is helpful in solving the problem that the IoT intrusion detection system cannot achieve high precision and low cost at the same time.
引用
收藏
页码:2119 / 2135
页数:17
相关论文
empty
未找到相关数据