Palo Alto, Calif. – March 10, 2016 — Fraud is costly and running rampant in online marketplaces, social networks and communities across the web. Effectively spotting and stopping fraud on a global scale requires determining the signals most closely correlated with fraudsters. Fraudsters vary in their methods, machines and machinations — but there are some commonalities and signals that point to likely fraud.
To provide a glimpse into some of the leading indicators of fraud, fraud detection provider Simility aggregated more than 100 different signals across 500,000 real world browser-based devices throughout January 2016. The fraud analysts looked for patterns in the 10,000 (or 2%) of those devices that were in the hands of fraudsters and contrasted those with the other 98% of devices in the hands of good or “organic” users.
Seven interesting anomalies emerged that were leading indicators of fraud:
1. 32-bit OS running on 64 bit processors: A transaction is 8x more likely to be fraudulent if the device configuration matches this description — often because fraudsters use “cracked versions” of older Windows machines which are imaged and then explicitly programmed for greater control like cookie cleaning.
2. Fresh cookies without old cookies: Fraudsters clear their cookies 90% of the time whereas organic users clear cookies only 10% of the time. Thus cookie age is a strong fraud signal, and unlike the baked items, browser cookies are more likely to be good the older they are.
3. Null values: There is another feature in browsers which is “Do Not Track” (http://donottrack.us/). For organic/real users the possible options are “Yes”, “No”, “Unspecified”; with “No” (70% of the times) as the default settings. With fraudsters on the other hand this value is often “null” which is not among possible organic values. There are more such browser configuration parameters where fraudulent devices have values other than the possible organic values.
4. Flushed browser referrer history: Fraudsters often flush their browser referrer history. <5% of the organic population explicitly filter their referrer history using third party plugins, extensions. Fraudsters as a population are 5x more likely to do this.
5. Bad apples don’t use Macs: While windows desktop and laptop have a dominant market share organically (90%+ overall) and 70%+ among our sampled data of users. Fraudsters tend to be heavy on windows over 96%+ fraudsters.
6. Fraudsters do not install a lot of plugins and extensions: They tend to “keep it simple” with 90% of fraudsters having less than 5 plugins in the browser. By comparison, good users have more plugins and in fact 1 in 20 of the organic population have more than 25 plugins/extensions installed — which is in a way risky and asking for trouble.
7. Fraudsters don’t go incognito: But it’s not just the fraudsters’ behavior that’s revealing. There is are also leading indicators for good users. For example, a user in “private mode” is more likely to be good than bad. Surprisingly, fraudsters do not enable private mode — in fact, organic users are 3x more likely to prefer private mode.
For more information on this and future Simility reports please visit: https://simility.com/blog/.
Simility is a cloud-based fraud prevention software solution that combines the power of machine learning and human analysis. Simility’s highly scalable platform protects SMBs and enterprise clients from the most sophisticated types of fraud. It also empowers fraud analysts to quickly adapt to fraudsters’ evolving tactics – all without having to write code. Built “by fraud fighters for fraud fighters,” the founding team’s combined 27 years of fighting fraud at Google puts them in a uniquely qualified class of fraud detection and prevention experts. Founded in 2014 with Headquarters in Palo Alto, Simility is backed by Accel Partners and Trinity Ventures. For more information, visit www.simility.com.