DataVisor raises $40 million Series C for machine

The company, founded by two former Microsoft Research employees, uses unsupervised machine learning to discover malicious behavior.

DataVisor, a company that uses machine learning to detect fraud, announced a $40 million Series C funding round Monday led by Sequoia Capital China.

The company, founded by two former Microsoft Research employees, uses unsupervised machine learning to discover malicious behavior. Unsupervised learning allows machines to track patterns across data sets in order to make decisions on their own, as opposed to supervised learning, which trains computers through data feeds provided by engineers.

DataVisor detects various types of fraud and abuse, including fraudulent transactions, fake content, spam and abuse, identity theft, application fraud and money laundering. The company says its technology protects 2 billion users globally, with a client list that includces Pinterest, Yelp, Alibaba Group, Dianping, Toutiao, Cheetah Mobile and Tokopedia.

“Enterprises today are facing constantly evolving threats from sophisticated and tech-savvy fraudsters who continuously experiment and find ways to evade detection,” said Yinglian Xie, CEO and co-founder of DataVisor. “This new round of financing will enable us to further improve our technology, expand our services globally and transform the way that businesses fight fraud.”

Fraud detection and prevention continues to be a flourishing market, expected to be worth $41.59 billion by 2022, according to research firm MarketsandMarkets. Government and public utilities are expected to be the highest growth sectors for the market, according to the research.

The round also included participation from existing investors New Enterprise Associates and GSR Ventures.

Government

• Feds accuse China of ‘systematic’ distillation of U.S. AI models

• CIA’s Michael Ellis says cyber intelligence is changing how the agency operates

• Jail time for Maine child in 764 marks turning point in federal law enforcement

• FCC proposes public scorecard to rate telecoms on anti-robocall efforts

Technology

• Pegasus, NoviSpy variant spyware found on devices of Serbian activists

• Wyden seeks upgraded NSA security guidance on commercial VPN use

• The Collective Cyber Defense letter wrote your next vendor questionnaire

• Former sexual abuse victims say Grok used their images, videos to train deepfake capabilities

Threats

• Chinese espionage groups swarm to exploit triple-link chain of zero-days

• Microsoft discloses two actively exploited zero-days among 974 vulnerabilities

• Russian national extradited to US for alleged involvement in bank-account takeover scheme

• Attackers exploit zero-days in consistently besieged SonicWall product

Policy

• Whistleblower says USPS deploying new, ‘untested’ IT systems governing mail-in ballots

• ‘Watershed 250’ test program in Texas looks to private sector for water cybersecurity help

• Cyber threats nudge Trump to sign executive order on foreign equipment in U.S. energy infrastructure

• Election official says Tina Peters would be consultant, won’t have access to election systems