I have prepared a small dataset based on the information Lyft and Uber would have used to identify the “DDoS” attacks. The data contains some 30 rides (canceled or not canceled) with the corresponding accounts, phone numbers…and IP addresses. Each order is linked to an account, accounts are linked to one phone number and one IP address. The articles on Lyft and Uber have not mentioned the IPs being used to detect suspicious activities but both companies could have used it.
The entire dataset has been loaded into Neo4j and can be downloaded here. Neo4j is a graph database and can be used to quickly find the connections between various entities, even in large datasets.
I have pulled up this data in Linkurious, the graph visualization tool we develop to understand what the people at Uber of Lyft may have experienced. In light green are IP addresses, in dark green phone numbers, in orange orders (with their dates displayed). The names represent the accounts.