This post is regarding the WPA2 4-way handshake that is used for authentication and the establishment of encryption keys for secure wireless communication. A practical implementation of the key derivation process is provided in python. The sample packet capture containing the 4-way handshake that is used in this post is available here. The complete source code discussed in this post is on Github. The software Wireshark is used to analyze the provided packet trace.
This post is part of a series on artificial neural networks (ANN) in TensorFlow and Python.
- Stock Market Prediction Using Multi-Layer Perceptrons With TensorFlow
- Stock Market Prediction in Python Part 2
- Visualizing Neural Network Performance on High-Dimensional Data
- Image Classification Using Convolutional Neural Networks in TensorFlow
This post revisits the problem of predicting stock prices based on historical stock data using TensorFlow that was explored in a previous post. In the previous post, stock price was predicted solely based on the date. First, the date was converted to a numerical value in LibreOffice, then the resulting integer value was read into a matrix using numpy. As stated in the post, this method was not meant to be indicative of how actual stock prediction is done. This post aims to slightly improve upon the previous model and explore new features in tensorflow and Anaconda python. The corresponding source code is available here.
Note: See a later post Visualizing Neural Network Performance on High-Dimensional Data for code to help visualize neural network learning and performance.