Network Intrusion Detection based on various machine learning and deep learning algorithms using UNSW-NB15 Dataset iotmachine-learningdeep-learningrandom-foresttensorflowlinear-regressionkerascybersecuritysupervised-learningclassificationlogistic-regressionknndecision-tree-classifieriot-securitysvm-classifiernetwork-securi...
Our experimental results showed the accuracy rate of the proposed method using DNN. It showed that accuracy rate is above 90% with each dataset.Previous article in issue Next article in issue Keywords IoT Internet of Things (IoT) Deep Neural Network (DNN) UNSW-NB15 KDD Cup’99 NSL-KDD ...
UNSW-NB15 datasetlogistic regressionsupport vector machinedecision treerandom forestThe rapid proliferation of new technologies such as Internet of Things (IoT), cloud computing, virtualization, and smart devices has led to a massive annual production of over 400 zettabytes of network traffic data. As...
Our experimental results showed the accuracy rate of the proposed method using DNN. It showed that accuracy rate is above 90% with each dataset. 展开 关键词: IoTInternet of Things (IoT)Deep Neural Network (DNN)UNSW-NB15KDD Cup’99NSL-KDDData set ...
物联网数据集CIC IoT Dataset 2023和(TON-IoT)、以及网络数据集UNSW-NB15 Dataset 私聊 CIC IoT Dataset 2023是由加拿大网络安全研究所提供的一个数据集,旨在促进物联网(IoT)环境中大规模攻击的安全分析应用程序的开发。该数据集包含33种攻击,分为7类,包括DDoS、DoS、侦察、基于Web的攻击、暴力破解、欺骗和Mirai...
Keywords: Machine learning, Feature engineering, Computer networks, Intrusion detection Introduction The rapid pace at which technologies such as the Internet, Internet-of-Things (IoT) and communication systems is advancing has caused hackers to evolve with a higher velocity in terms of their ...
ML-Based Intrusion Detection withFeature Analysis onUnbalanced UNSW-NB15 Datasetdoi:10.1007/978-981-97-6465-5_26Intrusion detection in modern networks, encompassing the Internet of Things (IoT), software-defined networking (SDN), and cloud environments, represents a pressing research challenge for ...
In this paper, we propose an hybrid model combining the convolution neural network (CNN) and the long short-term memory (LSTM) with hyper-parameters optimization using Bayesian optimization method for attacks detection in IoT. We train and test our hybrid model using the benchmark dataset UNSW-...
Systems, Internet of Things (IoT), SCADA, Industrial IoT, and Industry 4.0. The authors of the dataset have granted free use of the dataset for academic research purposes, while commercial use requires their approval. Usability info 7.06
About Dataset The raw network packets of the UNSW-NB 15 dataset was created by the IXIA PerfectStorm tool in the Cyber Range Lab of the Australian Centre for Cyber Security (ACCS) for generating a hybrid of real modern normal activities and synthetic contemporary attack behaviours. ...