The popularity of streaming services, digital and social media is constantly growing, which inevitably attracts the attention of fraud perpetrators. The dual layer protection provided by CyberSiARA ensures that fraud attacks are prevented, while the experience of the genuine user is unaffected. Real traffic flows without interruption, maintaining seamless customer engagement with the service. Suspicious accounts are eliminated, with future attacks deterred.
Prevent Data Scraping
Secure user information that creates revenue.
Prevent Spam and Phishing
Protect users from large-scale attacks involving spam and phishing.
Prevent Promotional Abuse
Stop fraud targeting the bonus offers intended to attract new customers.
Prevent Payment Fraud
Halt malicious access to transaction information and customer payments.
Prevent Large-Scale Re-Sale
Defend against the re-sale of free trial accounts.
Prevent Credential Stuffing
Eliminate fake account creation by streamlining the sign-up process.
Adaptive Protection
Powered by Machine Learning, the platform adapts to identify and confront every attack.
Fraud-Proof Buffer
Occupying the space between fraudster and business, the platform effectively shifts the attack surface and keeps your business secure.
Elimination of Attacks
Instances of automated and human-led attacks are drastically reduced.
Intuitive Challenges
Customised, intuitive interactive challenges meet suspicious activity of all levels of sophistication.
Increased Real Traffic
With fraud reduced, genuine traffic flow is visibly increased.
Remove Financial Incentive
Using gamification principles, the platform immediately renders any attack non-viable.Fraud attacks are not a static threat. They are constantly evolving in line with advancements in technology, and the development of new user experiences. This situation requires a flexible and adaptive fraud prevention solution.
The CyberSiARA platform delivers a dual-layer protection approach which enhances the user experience and promotes loyalty among genuine customers. Powerful analytics filter traffic based on learned patterns of behaviour. Suspicious traffic is subjected to a chain of gamification-based enforcement challenges that increase in complexity – trapping both automated and human fraudsters while draining them of resources.
