Python Programming
Export Tables from Access to PostgreSQL
This article describes how to export a table from Access DB to postgresql via excel and python.
March 14, 2023
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- mukiraz@mukiraz.com
With Contaki, which is a new generation and open-source operating system, protocols such as IPv6, 6LoWPAN, RPL, CoAP can be simulated with Cooja.
With Cooja, any number and protocol of IoT sensors can be added, the codes of these sensors can be changed, and even the codes of existing sensors can be added to Cooja. Figure 3.6 shows Cooja’s user graph interface. Node 1 in the simulation in Figure 3.6 is set to “root”. The other nodes are the “sensor”.
How to install Contiki Operation System and Cooja on Ubuntu 18.04 ?You can find answer and a good solution for this question in this page.
To run Cooja and do the experiments, I created a virtual machine with a VMWare Player with a capacity of 4 core processors, 16 GB of RAM, and 20 GB of Hard disk and installed the Ubuntu 18.04 operating system.
I used the following video during installation. If you want to install the Cooja simulator on your Ubuntu 18.04 machine, follow the step by step in the video below.
This article describes how to export a table from Access DB to postgresql via excel and python.
In this blog post, the Flooding Attack, Decreased Rank Attack and Version Number Increase Attack in the RPL protocol were trained and detected by “Decision Tree”, “Logistic Regression”, “Random Forest”, “Naive Bayes”, “K Nearest Neighbor” and “Artificial Neural Networks” algorithms.
The test results for the attacks were compared, as a result of the comparison, the Artificial Neural Networks algorithm with an accuracy rate of 97.2% in the detection of Flooding Attacks, the K Nearest Neighbor algorithm with an accuracy rate of 81% in the detection of Version Number Increase Attacks, and the Artificial Neural Networks with an accuracy rate of 58% in the detection of Decreased Rank attacks algorithm has been found to show success.
I continue to share how I did my master’s thesis titled Comparison of Machine Learning Algorithms for the Detection of Vulnerability of RPL-Based IoT Devices, my experiences in this process, and the codes in this thesis in a series of articles on my blog.
So far, I have provided detailed information about the RPL protocol and the attacks that take place in the RPL protocol. Then, I experimented with Flooding Attacks, Version Number Increased Attack, and Decreased Rank Attack, extracting the raw data and making sense of that raw data. I compared the results of experiments with weak knots with statistical methods.
In this section, I will interpret the numerical results of the attacks we detect with machine learning algorithms.