Cloud Computing: 5 ways to sniff out online fakers
October 4, 2012
Grazed from GigaOM. Author: Barb Darrow.
Sift Science says it can help you finger people on your website who are likely to create fraudulent accounts, post fake reviews or do other dastardly deeds. The startup’s service, now in private beta, uses machine learning to help ID the bad guys.
The problem of online fraud, fake reviews and sock puppetry is only going to get worse, according to recent research. But there are ways to identify likely perpetrators and that’s what Sift Science aims to do. The 8-person San Francisco startup uses machine learning to analyze user interaction with web sites and create a digital profile of who will likely perpetrate online fraud, said company co-founder Brandon Ballinger, an ex-Google software engineer…
Companies can use the service — built on Hadoop, HBase, Avro and MongoDB — by adding some Javascript code to their sites and then using JSON (JavaScript Object Notation) APIs “to track transactions, bans, chargebacks, or custom event types,” according to the company.
Here are some early finding based on the private beta of the service:
1: Fraudsters tend to be nightowls. Most fake accounts are created late at night local time: 3:00 a.m is apparently the witching hour…
Read more from the source @ http://gigaom.com/cloud/5-ways-to-sniff-out-online-fakers/