Data Availability Statement:

This data is bit-rate data from collected by streaming videos from YouTube. The data was collected using WireShark, and it measure the number of bits sent from server to client at 0.25 seconds intervals. Every video was streamed for exactly 20 minutes, so there are 4800 datapoints (a recording taken every 0.25 seconds at 20-minute intervals). The data is in CSV format and was read/written to and from CSV using the Python package PANDAS. In the CSV file, there are two columns: Time and Bytes. The time column increases at 0.25 increments and is a record of the time of the video at these increments. The Bytes column measures the number of bits at each time interval.

For example (Time: 0.25, Bytes: 1701) denotes that 1401 bits were sent from YouTube to the client 0.25 seconds into the video stream. In this dataset, we recorded data from 41 videos and each video was streamed 100+ times (some videos had over slightly 100 streams while others had exactly 100) so that the dataset has 4345 CSV files. The name of each file is the name of the video as it appeared on YouTube, without any spaces.

Presented and published in the IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2020) A full version was submitted to IEEE Transactions on Dependable and Secure Computing (IEEE TDSC).

The proposed scheme has been implemented using Solidity version 0.5.16 and deployed on Rinkeby Testnet (an Ethereum test network for test operations of smart contracts) with Truffle. The contract ID is "0xC48f9bb74ebaD1EEF59967b6e2Ba245f4D37F89C".

The nodes in a group are implemented using Node.js 10.16.3 including web3.js and Crypto modules to communicate with Blockchain and to utilize cryptographic functions.

Presented and published in the 29th International Conference on Computer Communications and Networks (ICCCN 2020).

This research presents a superior behavior-based anomaly detection system that defines authorized users' traffic patterns for enhanced network security.