Security

This FFT-75 dataset contains randomly sampled, potentially overlapping file fragments from 75 popular file types (see details below). It is the most diverse and balanced dataset available to the best of our knowledge. The dataset is labeled with class IDs and is ready for training supervised machine learning models. We distinguish 6 different scenarios with different granularity and provide variants with 512 and 4096-byte blocks. In each case, we sampled a balanced dataset and split the data as follows: 80% for training, 10% for testing and 10% for validation.

This dataset details the state machine based experiments of PowerWatch.

Website fingerprinting attacks, which use statistical analysis on network traffic to compromise user privacy, have been shown to be effective even if the traffic is sent over anonymity-preserving networks such as Tor. The classical attack model used to evaluate website fingerprinting attacks assumes an on-path adversary, who can observe all traffic traveling between the user's computer and the secure network.

The steganography and steganalysis of audio, especially compressed audio, have drawn increasing attention in recent years, and various algorithms are proposed. However, there is no standard public dataset for us to verify the efficiency of each proposed algorithm. Therefore, to promote the study field, we construct a dataset including 33038 stereo WAV audio clips with a sampling rate of 44.1 kHz and duration of 10s. And, all audio files are from the Internet through data crawling, which is for a better simulation of a real detection environment.