Common reports about data being sold on the dark web are inconsistent, inaccurate, and misleading, according to a meta-analysis report from the investigative team at Terbium Labs. The report, released Tuesday, examined the cost of data for sale on the dark web from 2013 until now, said the Tuesday press release.

Many researchers, cybersecurity firms, and media post reports and warnings about goods being sold in the dark web, in an effort to make companies aware of identity threat and fraud, said the release. However, after studying 22 reports, Terbium found “the inconsistent terminology and haphazard collection strategies used only add to an already confusing picture of the dark web,” according to the release.

SEE: IT leader’s guide to the Dark Web (Tech Pro Research)

Terbium’s research focuses on pricing data for online banking or social media accounts, as well as identity information like payment card data or Social Security numbers, said the release. The research found that the publicity surrounding data being sold on the dark web does more harm than good, as systematic inconsistencies in information just lead to fear and doubt in the enterprise, added the release.

Additionally, information about the dark web is cherry-picked and biased, leaving isolated examples with prices higher than normal, said the release. The reports also do not provide any insight into larger trends of pricing, the market as a whole, or the scale of actual data compromise, added the release.

Companies should not listen to publicized, incorrect data, said the release, and instead use a price index to measure sensitive data processing on the dark web. Through this, companies can better collaborate to defend against threats and decrease fraud risks, explained the firm.

“Instead of focusing on snapshots of pricing in time, Terbium Labs seeks to analyze fraud on the dark web economy at scale, focusing on the dynamics affecting the shifts in supply and demand,” said Munish Walther-Puri, chief research officer at Terbium Labs.

The big takeaways for tech leaders:

  • Information on the internet about data being sold on the dark web is often incorrect and misleading. — Terbium Labs, 2018
  • Researchers and cybersecurity vendors should create a universal classification system for data sold on the dark web, in order to prevent fear and worry caused by skewed information.