📡Intelligence

SMP Intelligence's role is to collect and analyze information for business support and security enhancement.

For example, integrating and analyzing on-chain and off-chain data enables data-driven business operations for businesses that utilize SMP. It can also be used for alerting sudden changes in token prices and for cyberattack prevention.

The Rationale Behind Handling both Business Support and Security Enhancement

Although providing support for business expansions and security measures to protect business stability may be implemented independently, this protocol treats them as part of an integrated intelligence strategy. The reason for this is that in addition to the aspect of improving convenience, rationality, and consistency via a comprehensive information-management system, we also recognize the social trend that the boundary between business and security is becoming blurred.

Businesses utilizing crypto assets are experiencing theft and malicious attacks on a daily basis. Meanwhile, these cyberattacks are becoming increasingly complex and international. The technology for regulation and policing is not developing fast enough to prevent them. In order to conduct stable businesses under these circumstances, self-protection is more important than ever before.

Of course, there is a limit to the ability of individual businesses to self-provide marketing strategies and security measures based on large-scale data. Therefore, SMP provides a myriad of Intelligence services for each business and users similar to the SMP Platform service group to ensure stable growth of the ecosystem.

Basic Functions of Business Support

(1) Assistance in Formulating Analytical Indicators

We identify items that need to be analyzed for each product, including on-chain and off-chain data.

In this case, it is necessary to create a KPI logic deciphering which factors are related to each other. We will break down the success factors that will lead to KGI (Key Goal Indicators) and how they are reflected in the KPI.

(2) Data Collection

On-chain data and off-chain data are connected via APIs and aggregated in a data integration infrastructure.

The data ranges from user behavior data within the service, engagement on social media, on-chain transactions, and personal wallet data.

Visualization and Utilization of Data

Aggregated data will be visualized through dashboards and real-time notification services showing the KPI logic defined in (1). For example, we provide functions such as price fluctuation notifications for various crypto assets, sales/user analysis, comparisons against competitive products, and social media/community data analysis.

These visualized data will facilitate data-driven decision making for business and marketing activities.

Necessity of On-chain and Off-chain Data Integration

In blockchain-based products, we can measure user engagement via in-service behavior, social media behavior, and on-chain transactions. Therefore, a composite analysis of off-chain and on-chain data is required when making data-driven management and policy decisions.

For example, each user's token holdings (number and duration of possession) can be an indicator of loyalty to the project, and usage within the service (frequency of transactions and mint/burn rate) can be an indicator of user activeness.

Interpretation of on-chain data will vary depending on the utility design of the NFT or FT and the ecosystem design.

Therefore, SMP Intelligence combines and visualizes on-chain and off-chain data to support data-driven management and policy decisions that are only possible in web3.

Basic Functions for Enhanced Security

Security risks that should be addressed include but are not limited to information leaks such as customer information and confidential information, asset leaks from businesses and user wallets, service outages due to DDoS attacks or malware, and information manipulation from fake news, etc…

To address these risks, we first provide data management functions to properly manage data authority and encryption. We are actively developing and investing in technologies related to secret sharing, MPC, threshold signatures, and other cryptographic technologies that can simplify data authority management.

In addition to machine learning techniques such as image recognition and large language models (LLMs), we are also engaged in technological research on real-time anomaly detection and potential system vulnerability detection, utilizing AI solutions based on formal verification and inference models.