Tencent Cloud Media and Entertainment Global

Zilong Game

Fraud Detection · Risk Management

Zilong Game needed to stop gold-farming and increasingly complex cheating in Ragnarok X: Next Generation before those behaviors destabilized the in-game economy, damaged PvP fairness, and weakened long-term player retention across global markets.

Reported impact

Business outcome

Zilong Game gained proactive protection for both cheating and economic abuse, helping Ragnarok X preserve fair competition, stabilize its in-game economy, and maintain player trust at global scale.

  • Customer Experience
  • Risk Reduction
  • Scalability

Solution

Zilong Game used Tencent Cloud to turn game security for Ragnarok X: Next Generation into a continuous detection system rather than a purely reactive response workflow. The deployment combines Tencent Cloud Anti-Cheat Expert with AI-powered protection models and dual-platform anti-cheat SDKs. Player behavior, economic activity, and client signals are monitored in real time; aggregated telemetry is analyzed to surface abnormal transaction chains and gold-farming behavior, while the SDK layer hardens both client environments against accelerators, memory modifiers, emulator abuse, and other exploit paths. The same setup supports earlier interception of black-market actors before inflation and unfair play spread through the title. By joining AI-based economic protection with client-side anti-cheat controls, Tencent Cloud gave Zilong a security architecture that protects both the gameplay loop and the virtual economy across large-scale live operations.

Data flow

Gameplay telemetry, transaction behavior, and client signals flow into Tencent Cloud's protection stack, where AI-powered models identify suspicious economic patterns and Anti-Cheat Expert plus deployed SDKs enforce protections against cheats, emulator abuse, and abnormal multi-endpoint activity.

Solution architecture

3 components · 3 layers
  1. Compute
    • AI-powered protection models Analyze aggregated gameplay and transaction behavior to identify abnormal economic activity and gold-farming patterns.
  2. Serving
    • anti-cheat SDKs Harden both client environments against emulator abuse, modified clients, and multi-endpoint cheating scenarios.
  3. Governance
    • Tencent Cloud Anti-Cheat Expert Provides the overarching anti-cheat protection layer for live Ragnarok X operations.

Architecture clues

  • The deployment is intended to catch abnormal transaction chains and black-market activity before they spread.
  • The design pairs AI-based economic analysis with dual-platform SDK hardening.
  • The publisher distributes titles in more than 30 global markets.

Evidence from the source

A dual-client hardening strategy was implemented by deploying anti-cheat SDKs across both platforms, blocking multi-endpoint cheating scenarios and preventing exploit attempts from emulators, modified clients, or alternative runtime environments.
AI-powered protection models analyze aggregated in-game behavioral data to accurately identify abnormal transaction chains and gold-farming patterns, safeguarding the stability of the in-game economy.
Pre-emptive threat detection based on real-time monitoring enables early interception of malicious actors, effectively raising the entry threshold for black market activities.
Tencent Cloud Anti-Cheat Expert transforms game security from reactive defense into proactive, intelligent protection, safeguarding fairness, economic stability, and long-term player trust at global scale.
Transparency Evidence & methodology 71/100 reference value · 79% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value71/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence79%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency10/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Tencent Cloud

    Ragnarok X | Tencent Cloud

    First-party
    https://intl.cloud.tencent.com/customers/detail/3563
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Region
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • Business outcome
    • Architecture
    • evidence quotes
Not separately sourced Industry, Company size, Metrics. Treat these normalized attributes as lower-confidence until a dedicated source is added.