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Lumino Secure Multi-Party Computing: A New Generation Of Data Security Sharing Solution

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The Dilemma Of Digital Economy

The most critical and cardinal element of the digital economy is data. Data is the “oil” of digital economy. Hence, utilizing the “data oil” safely and efficiently is the focal point of global economic digital transformation. On the one hand, the digital economy has entered a high-speed development age. The global digital economy has reached 36.2% of global GDP. It is necessary to open up the “data island” among enterprises and establish an open and shared digital resource environment. On the other hand, the public is paying more and more attention to personal privacy and data security, and regulators have introduced a series of regulations to ensure information security. For example, car companies buy parts back and assemble them into cars, the ownership belongs to the car companies, while parts manufacturers also make it clear that once the parts are sold to factories, the factories have ownership. But the data level is more sensitive. Personal data include the face, voice, name, height and other sensitive personal privacy specifics. How to define the ownership of the data between these parties? At present, there are no clear legal provisions, nor the industry has clear answers. In foreign practice, the EU has made very strict data protection regulations, but the entire EU data information technology industry lags behind China and the United States.

Because data protection is too strict, data from different sources do not interact, data is not open and can not interact to generate value and to improve the efficiency of the economy as a whole. The EU is not a good example, because it does not balance the relationship between data privacy protection and the development of the data industry.

Privacy protection and data security need multi-party promotion

Facing the dilemma of data security and sharing, the “available and invisible” secure multi-party computing provides us with an innovative solution.

Secure multi-party computing is a calculation process performed by multiple participants. Multi-party computing technology includes inadvertent transmission, secret sharing and confusing circuit. Multi-party computing has the advantage of high confidentiality and maneuverability, and each party has absolute control over the data it owns. Secure multi-party computing can be applied to networks where participants are not trusted. Participants can know the agreed results of collaborative computation, but they can’t get or deduce the original contents of the data. The flow of data and the collaborative analysis are of great value in all industries, and have brought about a lot of application demands. There are two main scenarios in the market:

1) Data security query

In the big data age, the data that the enterprise holds itself often cannot satisfy the demand of business analysis, many enterprises will purchase the external data to expand the data source. When an enterprise uses an external database to query, it faces the risk of divulging the query condition information. MPC technology helps enterprises to set up a secure query to obtain more external data under the condition of ensuring their own data security, thereby deepening the digital transformation and making better use of big data technology to optimize business.

2) Data joint analysis

Joint analysis often faces two headwinds. On one hand, it is illegal to trade personal privacy information. On the other hand, data sharing makes data-holding companies lose their competitive edge. MPC technology, through inadvertently querying, makes the data not public, the query object not exposed, and the results can be correctly given feedback for, which has an important application in the financial risk control business.

Lumino: new ideas for secure multi-party computing

Lumino is a large-scale activity that uses secure multi-party computing protocols to generate zero knowledge proof system public reference string (CRS) in a de-trust manner, and it is a prerequisite and an important step for deploying and using privacy-related applications in a decentralized ecosystem. The activity now focuses on the PLONK algorithm. As a practical and efficient zk-SNARK algorithm, PLONK is often used in blockchain projects and communities, which is characterized by only one-time initialization process, i. e. running once, it can be used to support a variety of underlying circuit logic and multi-class application deployment.

Lumino’s vision, from the start, was to link the world’s cryptographic geeks to become co-creators and witnesses of privacy computing infrastructure, not just an event but a ritual. We changed the method of centralizing system parameters into a distributed one. For a truly community-based and open-source blockchain ecosystem, each of which is the most critical link, and each participant who joins makes the bottom one safer, which would be a ceremonial collective wisdom.

Lumino is the cornerstone of subsequent de-centering privacy protection applications based on zero-knowledge proof, and the subsequent de-centralization applications will be safer only if the activity is safely completed.

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Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.

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Press Release

Global Publicist 24 Magazine Names Pharmacist and Entrepreneur Abadir Nasr as Cover Leader of Its 2026 “Most Influential Leader Shaping the Future of Business” Edition

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Global Publicist 24 Magazine, an international business publication that profiles influential leaders and high-impact entrepreneurs, has released its special 2026 edition, “The Most Influential Leader Shaping the Future of Business,” with pharmacist and healthcare entrepreneur Abadir Nasr featured on the cover.

The edition recognises leaders whose vision and execution are reshaping their industries, and Nasr was selected as the cover personality for his work building a community-focused pharmacy model centred on trust, accessibility, and patient care.

Nasr is the pharmacist and owner of Arvazy Pharma and Whitfield’s Guardian Pharmacy. Combining clinical training with hands-on business leadership, he has developed both pharmacies into local healthcare destinations known for personalised service and patient advocacy rather than transactional dispensing.

“Healthcare does not end at the counter when you hand someone their medication,” said Nasr in the cover feature. “It starts with understanding the person in front of you, and that relationship is what keeps a community healthy.”

Across both businesses, Nasr has applied a consistent philosophy: that meaningful patient relationships and sound commercial decisions can grow together. The cover feature traces his entrepreneurial path, the operational challenges he worked through, and his outlook on where pharmacy and community healthcare are heading.

Commenting on the selection, Sagar Kasar, Editorial Lead at Global Publicist 24, said: “Abadir represents the kind of leadership this edition was built to highlight. He has grown a healthcare business while keeping patient trust at the centre of every decision, and that balance is genuinely difficult to achieve.”

The 2026 edition also features leaders from a range of industries whose work in innovation, growth, and customer-focused strategy offers practical lessons for founders and executives navigating a fast-changing economy.

The new edition of Global Publicist 24 Magazine is available now to readers worldwide.

About Global Publicist 24 Magazine

Global Publicist 24 Magazine is an international business publication that profiles influential leaders, innovative organisations, and notable success stories worldwide through exclusive interviews, thought-leadership features, and industry analysis.

Website: https://www.globalpublicist24.com/magazines/
Email: info@globalpublicist24.com
Phone: (+1) 302 956 1687

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Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.

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Press Release

Dataline Launches Data Launch Partner Program to Power the Next Generation of AI Trading and Onchain Agents

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British Virgin Islands, BVI, June 2026, ZEX PR WIREDataline, the data infrastructure layer for AI agents operating across crypto and financial markets, recently announced the launch of its Data Launch Partner Program, opening access to an initial cohort of AI systems, trading agents, and data providers building on its unified intelligence layer.  

  

As AI agents increasingly move from chat-based interfaces to autonomous decision-making systems, the need for structured, cross-market, and verifiable financial data has become a foundational bottleneck. Dataline closes this gap by unifying distributed market data into a schema-based layer, with each response carrying an AI-generated confidence score so the agent can judge for itself whether to act on it.  

A Unified Data Layer for Agent Economies

Dataline connects real-time data across major centralised exchanges, decentralised protocols, and prediction markets, including Binance, Coinbase, OKX, Hyperliquid, dYdX, Polymarket, and Kalshi, into a single structured response format.  

Each query is processed through a cross-venue normalisation system that aggregates pricing, funding rates, liquidity conditions, and event-based signals into confidence-scored outputs with source-level traceability and freshness indicators. 

This allows AI agents to operate on consistent, verified inputs rather than fragmented or venue-specific APIs.  

From Data Access to Decision Infrastructure

The evolution of AI agents has shifted the industry focus away from blind execution and toward interpretation.  

Dataline’s system is designed to solve this by providing the following:  

  • Cross-venue data normalization across trading and prediction markets

  • Confidence-scored outputs with divergence detection between sources

  • Structured responses optimized for planner–executor–verifier agent loops

  • Real-time aggregation of market signals and event data

Already Powering Live Agent Systems

Dataline is already deployed in production environments, supporting over 19.4 million on-chain transactions across the Base, BNB Chain, Sui, and the TON ecosystem.  

Agent systems built on top of Dataline — including ChatPilot, GhostDriver, and FlowAgent — are actively using its structured data layer for live trading, signal processing, and autonomous execution workflows.

Launch Partners Across AI and Execution Layers

The initial Data Launch cohort includes partnerships with AI agent frameworks and execution infrastructure providers such as Sentient, Kite AI, B3, Fraction AI, and Sahara AI.  

These integrations reflect a growing ecosystem where AI agents not only interpret financial data but also execute transactions across programmable settlement layers in real time.  

Exclusive Offer for Base Builders

To support the growing community of builders on Base, Dataline is offering six months of free data feeds to qualifying Base projects. Teams building on Base can claim the offer by reaching out to @datalineai on X and introducing their project.  

Accelerating the Shift Toward Agent-Native Financial Infrastructure

As AI systems become embedded in financial decision-making, industry infrastructure is shifting from API-centric models toward schema-based intelligence layers capable of unifying siloed markets.  

As part of this transition, Dataline enables agents to operate across fragmented environments through a unified execution layer, without requiring venue-specific logic or manual reconciliation.  

Become a Dataline Launch Partner

Dataline is expanding its Data Launch Partner cohort. Projects interested in integrating Dataline’s data layer or joining the program can reach out to @datalineai on X to start the conversation.  

About Author

Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.

Continue Reading

Press Release

Dataline Launches Data Launch Partner Program to Power the Next Generation of AI Trading and Onchain Agents

Published

on

British Virgin Islands, BVI, June 2026, ZEX PR WIREDataline, the data infrastructure layer for AI agents operating across crypto and financial markets, recently announced the launch of its Data Launch Partner Program, opening access to an initial cohort of AI systems, trading agents, and data providers building on its unified intelligence layer.  

  

As AI agents increasingly move from chat-based interfaces to autonomous decision-making systems, the need for structured, cross-market, and verifiable financial data has become a foundational bottleneck. Dataline closes this gap by unifying distributed market data into a schema-based layer, with each response carrying an AI-generated confidence score so the agent can judge for itself whether to act on it.  

A Unified Data Layer for Agent Economies

Dataline connects real-time data across major centralised exchanges, decentralised protocols, and prediction markets, including Binance, Coinbase, OKX, Hyperliquid, dYdX, Polymarket, and Kalshi, into a single structured response format.  

Each query is processed through a cross-venue normalisation system that aggregates pricing, funding rates, liquidity conditions, and event-based signals into confidence-scored outputs with source-level traceability and freshness indicators. 

This allows AI agents to operate on consistent, verified inputs rather than fragmented or venue-specific APIs.  

From Data Access to Decision Infrastructure

The evolution of AI agents has shifted the industry focus away from blind execution and toward interpretation.  

Dataline’s system is designed to solve this by providing the following:  

  • Cross-venue data normalization across trading and prediction markets

  • Confidence-scored outputs with divergence detection between sources

  • Structured responses optimized for planner–executor–verifier agent loops

  • Real-time aggregation of market signals and event data

Already Powering Live Agent Systems

Dataline is already deployed in production environments, supporting over 19.4 million on-chain transactions across the Base, BNB Chain, Sui, and the TON ecosystem.  

Agent systems built on top of Dataline — including ChatPilot, GhostDriver, and FlowAgent — are actively using its structured data layer for live trading, signal processing, and autonomous execution workflows.

Launch Partners Across AI and Execution Layers

The initial Data Launch cohort includes partnerships with AI agent frameworks and execution infrastructure providers such as Sentient, Kite AI, B3, Fraction AI, and Sahara AI.  

These integrations reflect a growing ecosystem where AI agents not only interpret financial data but also execute transactions across programmable settlement layers in real time.  

Exclusive Offer for Base Builders

To support the growing community of builders on Base, Dataline is offering six months of free data feeds to qualifying Base projects. Teams building on Base can claim the offer by reaching out to @datalineai on X and introducing their project.  

Accelerating the Shift Toward Agent-Native Financial Infrastructure

As AI systems become embedded in financial decision-making, industry infrastructure is shifting from API-centric models toward schema-based intelligence layers capable of unifying siloed markets.  

As part of this transition, Dataline enables agents to operate across fragmented environments through a unified execution layer, without requiring venue-specific logic or manual reconciliation.  

Become a Dataline Launch Partner

Dataline is expanding its Data Launch Partner cohort. Projects interested in integrating Dataline’s data layer or joining the program can reach out to @datalineai on X to start the conversation.  

About Author

Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.

Continue Reading

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