Spam & Fake Reviews

Maintain Authenticity as You Grow

Spam and fake reviews have become a ubiquitous problem for social and ecommerce brands. To become economically viable, fraudsters mount large scale attacks. To circumvent traditional rules-based solutions, they employ sophisticated attack techniques. Using an unsupervised machine learning approach, DataVisor’s solution excels in detecting unknown attacks and malicious accounts acting in a coordinated fashion. DataVisor can also detect correlated incubating events at account registration time to detect malicious accounts early before they can affect the integrity of your business.

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Common Attack Techniques

Content scraping

Attackers steal photos and content from other 3rd party social networking sites to appear authentic to content security measures

Mechanical turks

Cybercriminals employ armies of low-cost human labor to create more realistic reviews and spam messages

Account incubation

Fraudsters create and incubate fake accounts for lengthy periods of time to evade rules on account age

IP obfuscation

Fraudsters utilize proxies, VPN or cloud-hosting services to hide their tracks from IP blacklists and rules-based systems

DataVisor Online Fraud Report

Learn about the techniques fraudsters use to evade detection

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Why Unsupervised Machine Learning

As spam and fake review attack techniques evolve, traditional detection solutions that rely on content security or rules-based models are becoming less effective in capturing unknown, large-scale attacks. Combined with the latest big data technologies, our unsupervised machine learning algorithm is able to efficiently find coordinated user accounts among massive amounts of data.

Unknown threat protection

Detect new categories of attack campaigns without any training data or labels

Unparalleled accuracy and coverage

Uncover linkage among malicious accounts to catch all members of the crime ring

Early detection

Detect malicious accounts at account registration before any downstream damage is done

Key Features

User investigative console

Investigate bad actors, create detailed forensic reports and see threat trends with campaign visualizations

Automated Rules Engine

Automatically create and sunset new rules to upkeep rule effectiveness and detect abuse before it spreads

Real-time detection

Integrate using our Results API to reduce the window of exposure from threats by detecting bad actors in real-time

Account linkage view to discover hidden links among malicious accounts

Bringing Real Value to Our Customers


Learn how Yelp Stops Fake Accounts with DataVisor

The epidemic of fake accounts impacts businesses from social media to ecommerce to banking. Interested in knowing how to overcome this emerging threat? Watch this recording of a webinar hosted by Julian Wong, Technical Architect at DataVisor, and his special guest, Jim Blomo, Director of Engineering at Yelp, to learn how Yelp stops fake users while connecting people with local businesses.

Watch Recording

Getting Started

Want to get started and find out how DataVisor can help find malicious accounts hiding inside your online service? Request a security assessment today!

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