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WarRin Protocol: A point-to-point anonymous privacy communication system

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Dr.WarRin

www.bitcointalk.org

Summary

This white paper provides an explanation of the WarRin protocol and related blockchain, point-to-point, network value, transport protocol, and encryption algorithms. The limited space will highlight the WRC allocation scheme and purpose of the WarRin Protocol Token, which is important for achieving the WRC’s stated objectives.  This white paper is for informational purposes only and is not a promise of final implementation details. Some details may change during the development and testing phases. 

1.  Introduction

Traditional centralized communication systems such as WeChat,WhatsApp, FacebookMessage,Google  Allo,Skype face a range of problems, including government surveillance, privacy breaches, and inadequate security, and the WarRin protocol proposes apoint-to-pointencrypted communications system that leveragesblockchain technology, combined  with Double Ratc het algorithms, pre-keys, and extended X3DH handshakes. The WarRin Protocol uses The Generalized Directional Acyclic Graph  and Curve25519,AES-256,  and HMAC-SHA256  as the pronamor, allowing each account to have its own unique account chain, providing unlimited instant communication between points and unlimited scalability, anonymity, integrity, consistency, and asynchronousness. 

2. WarRin Protocol communication system

2.1 Two types of communication

The Waring Protocol communication system divides chat channels into two types.

Image

Two modes of communication

  • General Chat mode: Using point-to-point encrypted communication, the service side has access to the key and can log in via multiple devices. 
  • Secret Chat mode: Encrypted communication using point-to-point can only be accessed through two specific devices. 

The design combines some of the advantages of raiBlocks    multi-chain construction with IOTA/Byteball  DAG, which we call the Waring protocol. With improvements, we have given the WarRin protocol greater throughput and faster processing power while ensuring the security of the ledger, and network nodes can store the ledger in less space and search their communications accounts quickly in the ledger.  When two users communicate, third parties contain content that neither manager can access. When a user is chatting in secret, the message contains multimedia that can be designated as a self-destruct message, and when the message is read by the user, the message is automatically destroyed within the specified time. Once the message expires, it disappears on the user’s device. 

2.2 How chat history is encrypted

2.2.1 MTProto  Transport Protocol

Image

MTProto transport protocol

The WarRin communication system draws on RaiBlocks’ multi-chain structure for point-to-point communication. Each account has its own chain that records the sending and receiving behavior of the account. For example, in Figure 1,   there are 7  accounts, each with 7 chain records of the account sending and receiving communications. On the graph, horizontal coordinates represent the timeline, and portrait coordinates represent the index of the account. 

Transferring information from one account to another requires two transactions: one to send a communication from the sender’s transfer content, and one to receive information to add that content to the content of the receiving account. Whether in a send-side account or a receiving account, a PoW proof of work with the previous communication content Hash is required to add new communications to the account.  In the account chain, poWwork proves to be an anti-spam communication tool that can be done in seconds. In a single account chain, the Hash field of the previous block is known to pre-generate the PoW required for subsequent blocks. Therefore, as long as the time between the two communications is greater than the time required to generate the PoW, the user’s transaction will be completed instantaneously. 

In such a design, only the receiving end of the communication is required for settlement. The receiving end places the received communication signature on the account chain, which is called accepted communication. Once accepted, the receiving end then broadcasts the communication to the ledger of the other nodes. However, there may be situations where the receiving end is not online or is subject to a DoS   attack, which prevents the receiving end from putting the receiving side communication on the account chain, which we call uncommoted transactions. The X symbol in Figure 1 represents an open transaction sent from Account 2 to Account 5.  

Image

Obviously, because only the sending and receiving sides of the communication are required to settle, such communication is very lightweight, all traffic can be transmitted in a UDP package and processed very quickly. At the same time, all communications in an account are kept in one chain, with great integrity, and the ledger can be trimmed to a minimum. Some nodes are not interested in spending resources to store the full communication history of the account;   They are only interested in the current communications for each account. When an account communicates, its accumulated information is encoded, and these nodes only need to keep track of the latest blocks so that historical data can be discarded while maintaining correctness. Such communication is only possible if the sending and receiving sides trust each other and are not the final settlement of the entire network consensus. There is a security risk in the absence of trust on the sending and receiving ends, or in situations where the receiving end is attacked by DoS without the sender’s knowledge. 

We have observed that although each account has a separate chain, the entire ledger can be expressed in the form of a WarRin object. As shown in Figure 2, this is represented by the WarRin astros trading on all accounts in Figure 1.  

Image

The first unit in the WarRin object is the Genesis unit, the next six cells represent the allocation of the initial token, and the other units correspond to the communication transactions between the account chains. We use the symbol a/b to represent a communication transaction, where the sender is a andthe recipient is b. The last  4/1 unit in Figure 2 is the last communication corresponding to Figure 1  – sending communication from account 4 to account 1. A transaction in Figure 1 is a confirmation of the latest block or the latest communication on the account chains of both parties to the communication, reflected in Figure 2 as a reference to the latest units of the account chains of both parties to the communication. Take unit 4/1, for example, where the latest  block on account 4 was the receiving block for 2/4  trades and the newest block on  account 1 was the send block for 1/5 trade. So on the DAG, the 4/1 cell refers to the 2/4 cell and the 1/5 cell. 

The WarRin protocol uses triangular shrapned storage technology to crack impossible triangles in the blockchain through the shrapghine technology, with extensive node engagement and decontalination  while maintaining high throughput and security:

  • Complete shraping of blockchain status;
  • Secure and low-cost cross-synth trading;
  • Completely random witness selection;
  • Flexible and efficient configuration

Complete decentralization ensures absolute security and scalability of the standard chain.

(Figures   above show seven Ling-shaped objects:2/1 one;3/2  one… )

2.2.2 Curve25519 Elliptic Curve Encryption Algorithm

Curve25519,  proposed by Daniel Bernstein, is anelliptic  curve algorithm for the exchange of The Montgomery Curve’s Difi Herman keys. 

Montgomery Curve Curve Mathematical Expression: 图片图片

Curve25519 Curve Mathematical Expression:图片

Curve25519  encryption     algorithms are    图片 used for standard private and public keys, and the private keys used for Curve25519  图片 encryption algorithms are typically defined as secret 图片 indices, corresponding to 图片public  keys, coordinate points, which are usually sufficient to perform ECDH (elliptical) and symmetrical  elliptic curve encryption algorithms. If one party wants to send information to the other party and the other party has the 图片 public 图片and private keys, perform the following 图片calculation:

Generate a one-time random secret 图片图片   图片 index, calculated using Montgomery, because the message is a symmetrical password encrypted using 256-bit  sharing, such as AES  using a 256-bit integer 图片 one-time public key,  as akey, and 256-bit integer is a 图片prefix to encrypted information. Once a party to   图片图片图片the public 图片key receives this message, it can start by calculating , that is ,图片the receiver recovers the shared secret and 图片is able to decrypt the rest of the information. 

3. Incentives

On the basis of the WarRin agreement, by adding the incentive layer, we can effectively avoid the whole network being attacked and eliminate spam. As long as honest nodes control most of the calculations, for an attacker, the network is robust because of its simplicity of structure, and nodes need little coordination to work at the same time. They do not need to be authenticated because information is not sent to a location. 

3.1 WRC Certificate

WRC issued a total of 2,500,000 pieces and continued to increment according to the WoRin gain function. 

3.1.1 WoRin Gain Function

Image
Image

3.1.2 WoRin gain function control table

The WoRin gain function is compared to the table
Number of layers /F Growth factor /I WRC circulation
[1,50] 0.002 334918.8057
[51,100] 0.002 780024.2108
[101,150] 0.004 1177129.617
[151,200] 0.006 1487860.923
[201,250] 0.01 1722637
[251,300] 0.016 1894309.216
[301,400] 0.03 2101623.789
[401,500] 0.06 2217555.464
[501,1000] 0.1 2450712.257
[1001,2000] 0.12 2557457.3

According 图片to the Gain function, the 图片larger the number of layers, 图片the greater the growth rate, the faster each layer is filled, and the 图片greater the circulation. 

3.2 Allocation

Image

WarRin protocol node distribution

3.2.1 Node allocation

Set the initial price  图片  图片图片to 0.02,the layer where the first node is located is , according to the equation of the iso-difference column, there is , so that the 图片node token is assigned to the piece, for the price of 图片 the layer where the node 图片is located, there is a 图片图片set. 

For example, the number of tiers in which the  98th  node is located is Tier 13,  and the price of Tier 13 is 0.214,the tokens assigned by Tier 98 are 图片

3.2.2 Total number of address assignments

Each node occupies one address, and the total number of 图片addresses is

4. The use

WRC is the native pass-through of the WarRin protocol, andWRC will assign to Genesis nodes according to the above allocation scheme, which together form the entire network, andWRC can be used in the following scenarios, including but not limited to:

Pay the network’s gas charges, i.e. for transferring money and invoking smart contracts;

System Staking tokens, used for node elections and token issues;

The capital is lent to the validator in exchange for the amount of the reward;

Voting rights for system proposals;

The means of payment for apps developed  on WoRin Services;

WoRin Storage is a means of payment on the decentralization storage;

WoRin DNS domain name and WoRin  WWW website means of payment;

WoRin Proxy agents hide the means of payment for body and IP addresses;

WoRin Proxy penetrates payment methods reviewed by local ISPs

……

5. Conclusions

Metcalfe’s Law states that thevalue of a network is equal to the square of the number of nodes within the network, and that the value of the network is directly related to the square of the number of connected users. That is 图片( the 图片value factor, the number of 图片users.)  That is, the greater the number of users on a network, the greater the value of the entire network and each computer within that network. The WarRin protocol also follows this law, and when the number of nodes reaches a certain level, the entire network becomes more robust. 

References

[1] K. Birman, Reliable Distributed Systems: Technologies, Web Services and

Applications, Springer, 2005.

[2] V. Buterin, Ethereum: A next-generation smart contract and de- centralized

application platform, https://github.com/ethereum/wiki/wiki/White-Paper,  2013.

[3] M. Ben-Or, B. Kelmer, T. Rabin, Asynchronous secure  computa-  tions  with

optimal resilience, in Proceedings of the thirteenth annual ACM symposium on

Principles of distributed computing, p. 183–192. ACM, 1994.

[4] M. Castro, B. Liskov, et al., Practical byzantine fault tolerance, Proceedings of the

Third Symposium on Operating Systems Design and Implementation (1999), p. 173–

186, available at http://pmg.csail.mit.edu/papers/osdi99.pdf.

[5] EOS. IO, EOS. IO technical white paper,

https://github.com/EOSIO/Documentation/blob/master/TechnicalWhitePaper.md,

2017.

[6] D. Goldschlag, M. Reed, P. Syverson, Onion Routing for  Anony-  mous  and

Private Internet Connections, Communications of the ACM, 42, num. 2 (1999),

http://www.onion-router.net/Publications/CACM-1999.pdf.

[7] L. Lamport, R. Shostak, M. Pease, The byzantine  generals  problem, ACM

Transactions on Programming Languages and Systems, 4/3 (1982), p. 382–401.

[8] S. Larimer, The history of BitShares,

https://docs.bitshares.org/bitshares/history.html, 2013.

[9] M. Luby, A. Shokrollahi, et al.,  RaptorQ  forward error correction scheme for

object delivery, IETF RFC 6330, https://tools.ietf.org/html/rfc6330,  2011.

[10] P. Maymounkov, D. Mazières,  Kademlia: A peer-to-peer  infor-  mation  system

based on the XOR metric, in IPTPS ’01 revised pa- pers from the First International

Workshop on Peer-to-Peer Systems, p. 53–65, available at

http://pdos.csail.mit.edu/~petar/papers/ maymounkov-kademlia-lncs.pdf, 2002.

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Physical AI Lab Nature Will Unveils Natura-1, First General Foundation Model for the Physical World

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Prioritizing dexterous workflow and zero-shot instruction following, the Natura-1 is Nature Will’s first Physical General Foundation Model aimed at pioneering advanced robotics applications

SAN FRANCISCO, CA, United States, 16th Oct 2026 – Nature Will, a physical AI lab dedicated to building physical AGI, today announced the launch of Natura-1, a 50-billion-parameter physical general foundation model for dexterous hand control and zero-shot instruction following in advanced robotics applications. Pre-trained on over 1 million hours of egocentric human data, the Natura-1 combines instruction following with the ability to manipulate to changing task conditions and sustained actions over extended interactions, bringing the versatility of the hand within reach of a model that connects human intent to physical action.

With the rapid advancements in general AI and large language models, AI models developed for physical applications represent the next frontier in technological progress. Natura-1 showcases that generalization and fine physical control can be learned together in a foundation model for dexterous hands, applicable to any field where fine or delicate manipulations are required as part of the creation process. Built on a 50 billion parameter mixture-of-experts model trained jointly on language, images, video, and action, Natura-1 operates at a 100-millisecond control loop to unify language, vision, and high-degree-of-freedom action that connects language-directed behavior with the physical control.

“We believe general models that can handle every task must exist, and that those models must utilize dexterous hands,” said Ning Ding, CEO of Nature Will. “Natura-1 is our first step towards models that scale from human experience, building infrastructure that enables us to create the model from the ground up and that allows it to scale to any application. The Natura-1 is a 50-billion-parameter mixture-of-experts model with dexterous manipulation, long-horizon execution, and zero-shot instruction following, making it truly capable of scaling human experience into purposeful action.”

The model represents Nature Will’s first physical foundation model that is capable of general-purpose dexterous manipulation using real hardware, acting as a breakthrough in the development of general foundation models made to interact in the real world. Designed to scale, the model autonomously executes sustained, continuous workflows and follows complex natural language instructions, enabling it to reason through spatial constraints, multi-object relationships, and negative conditions.

For more information about the Natura-1, please read the official blog at https://www.naturewill.ai 

About Nature Will

Nature Will is a research-driven organization dedicated to building the physical artificial general intelligence. Focusing on training general-purpose foundation models, its team is working to develop models capable of closing the loop across perception, prediction, reasoning, and action in the real world, while exploring how embodied agents can achieve self-awareness and continuous learning within physically native environments. Nature Will’s R&D stack spans data acquisition and governance, foundation model pretraining, infrastructure, simulation and real-world evaluation, post-training, and reinforcement learning. Led by Founder and CEO Ning Ding, the company has assembled a full-stack physical AI team whose core members include frontier researchers, core contributors to flagship foundation models, champions of international student supercomputing competitions, and senior robotics hardware engineers.

To learn more about Nature Will, please visit https://www.naturewill.ai/

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Trumpery Times Launches Satirical Humor Website Featuring Fictional Characters and Parody Stories

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Trumpery Times has launched as a satirical website publishing fictional stories and parody articles about entertainment, internet culture and modern media. Every story is clearly labeled as fiction.

Sheridan, Wyoming, United States, 16th Oct 2026 – Trumpery Times has launched as a satirical digital publication that uses parody, exaggeration and fiction to present fictional stories about entertainment, internet culture and popular media. The website is now live at https://trumperytimes.com and is publishing its initial collection of fictional stories and invented profiles.

The publication borrows the familiar language of online media, including headlines, interviews, profiles and feature stories, and uses it as the format for its humorous fiction. Each story begins with a recognizable cultural idea and then develops it into a fictional storyline. All characters, events and situations on the site are fictional and are presented as satire, not as factual reporting.

Coverage includes celebrity culture, film, popular culture and the media industry itself. The publication is written for readers who enjoy satire and parody related to entertainment and media. Familiar formats such as headline-driven stories, celebrity profiles and entertainment features serve as the framework, while the content inside them is invented.

“Satire relies on recognizable subject matter,” said Lucas Komerlin, founder of Trumpery Times. “Readers need to recognize the starting point before the story moves into fiction. Trumpery Times starts with familiar subjects and develops them into fictional stories.”

That approach shapes how every story on the site is built. A familiar idea provides the starting point, and exaggeration is used to develop the story. As the story develops, the connection to reality gradually loosens until the situation on the page is clearly invented. The goal is for readers to recognize where a story began while following how the story develops.

“Each story begins with a familiar idea and then develops into an invented situation,” said Komerlin. “The challenge is deciding how far that idea can be extended while keeping a clear connection to what inspired it.”

The publication’s tagline, “Don’t Believe Everything You Read,” reflects the purpose of the publication. It signals that the site is built for entertainment and that its stories are not intended to be taken as news. Stories are written as clearly labeled fiction, and the familiar formats of media are used as a creative device, not as a way to mislead.

“The intention is not to disguise fiction as news, but to use the familiar language of news and popular media to create satire,” said Komerlin.

Trumpery Times combines recognizable cultural references with fictional characters, invented situations and exaggerated narratives, organized around entertainment, film, popular culture and media-themed features.

Trumpery Times aims to give readers a space where familiar parts of contemporary culture appear in fictional and exaggerated forms. Visitors can browse the initial collection of satirical stories and fictional profiles through the website.

About Trumpery Times

Trumpery Times is a satirical digital publication covering entertainment, popular culture and modern media through parody, exaggeration and fictional storytelling. The publication presents familiar cultural ideas through fictional storylines and invented characters. Trumpery Times is operated by Raya Do Yaya LLC. Its guiding principle is simple: “Don’t Believe Everything You Read.” For more information, visit https://trumperytimes.com.

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Wingsure Launches Coffee Intelligence to Turn Verified Farm Evidence Into Decision-Grade Insights

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Wingsure COFFEA is a deep-tech platform that creates a reusable farm intelligence layer for sustainability, sourcing, production, compliance, risk and finance while helping growers build value from their own farm records.

 

pasted or uploaded image

Image caption: Avi Basu, Founder, CEO, Wingsure

NEW YORK, September 2026: Wingsure, a deep-tech agricultural intelligence company and SRI spinout built on foundational technology developed with SRI, announced on September 28, 2026, the launch of Wingsure COFFEA, a platform that captures and verifies farm-level evidence and turns it into decision-grade intelligence for the global coffee sector.

Coffee connects millions of smallholder farms across diverse growing regions with a global market facing mounting climate risk, productivity challenges and sustainability requirements. Companies increasingly need credible farm-level intelligence to support traceability and deforestation safeguards, strengthen sourcing, understand production and quality, manage risk, support growers and make better-informed investment decisions.

Today, the same farm may be assessed separately for sustainability, sourcing, production, certification, finance and risk. This can create repeated work for growers while leaving enterprises with fragmented and often static views of farm conditions. Wingsure COFFEA takes a different approach: capture evidence at the farm, verify it at the source, build the farm record over time, and make that intelligence reusable across multiple programmes and business decisions. 

pasted or uploaded image

“What excites us about coffee is the opportunity to bring years of foundational deep-tech work to one of the world’s most important agricultural ecosystems – and to do it in a way that creates value on both sides of the farm gate,” said Avi Basu, Founder and CEO of Wingsure. “We have been fortunate to learn alongside some of the most respected organizations and people in coffee. One lesson has become very clear: a farm cannot be understood through a periodic form, a declaration, or a satellite image alone. It is a living system.”

“Our job is to turn what is happening on that farm into trusted intelligence that gets better over time. For the grower, that means a farm record that becomes more valuable with every season. For the enterprise, it means a common intelligence foundation for better decisions across sustainability, sourcing, production, risk and finance.”

For growers, the platform is designed to ensure that their knowledge, observations and actions do not disappear into disconnected surveys and programs. A farm record can become progressively more useful, helping growers demonstrate practices and progress, receive more relevant advisory support and, through participating in programmes, connect verified information with economic opportunities such as incentives, insurance and credit.

Using the smartphone already in a grower’s hand, Wingsure combines augmented-reality guided capture, multilingual voice capabilities, agronomic knowledge, computer vision, geospatial analytics, artificial intelligence and machine learning. Field observations can be geotagged, timestamped and converted into machine-readable records, including in offline environments. Satellite and drone context can further enrich the farm record.

“AI is only as credible as the evidence beneath it,” said Dr. Bikram Sengupta, Co-founder and CTO of Wingsure. “Our architecture keeps every insight connected to what was captured, where and when. That allows verification, inference and prediction to become part of one traceable intelligence system. The goal is not simply more data. It is intelligence you can trust.”

Together, these capabilities create a living intelligence layer spanning crop condition, farming practices, production signals and risk. Instead of becoming another isolated point solution, the platform is designed to support existing enterprise sustainability, sourcing, traceability, carbon, finance and risk systems by giving them a stronger, evidence-grounded understanding of the farm.

Perspectives from leaders across the coffee and agricultural risk ecosystem working with Wingsure underscore the importance of trusted farm-level intelligence in supporting growers, strengthening agricultural systems and improving enterprise decision-making.

Álvaro Gaitán, Technical Manager of the Colombian Coffee Growers Federation (FNC), one of the world’s most influential producer-led coffee organizations, representing more than half a million coffee-growing families in Colombia and behind the globally recognised Juan Valdez® brand, said:

“As a grower-led institution, FNC is focused on building the next generation of capabilities Colombian coffee producers will need to compete globally. Better, more timely farm intelligence is central to that vision. We are engaging with Wingsure to explore how its technology can complement FNC’s existing capabilities and help strengthen the coffee ecosystem for Colombian growers.”

From the agricultural risk and financial services side, Madhukar Sinha, President – Govt & Rural Business, Tata AIG General Insurance Company Ltd., one of India’s leading private general insurers and a joint venture between the Tata Group and AIG, said:

“Agricultural insurance has an important role to play in building farmer resilience, but achieving that at scale requires a much clearer and more timely understanding of what is actually happening at the farm. Wingsure’s approach is compelling because it connects verified field evidence with the intelligence needed for risk assessment and decision-making. The ability to create a trusted, continuously developing record of the farm can be valuable not only for insurance, but across the broader agricultural ecosystem. We believe Wingsure is addressing an important challenge with technology that has the potential to operate at a meaningful scale.”

The launch builds on Wingsure’s work across coffee and other crops to capture, verify, and analyse farm-level information for applications including crop health monitoring, damage and loss assessment, regenerative and sustainable practices verification, production and risk intelligence, agricultural insurance and credit. The platform traces its origins to computer vision and augmented reality technology developed by Wingsure in collaboration with SRI.

In coffee, Wingsure is extending this foundation into yield intelligence and coffee science applications, supported by real-world validation. Over time, each observation, intervention, and season compounds the intelligence around the farm – creating a persistent foundation from which new questions can be answered without rebuilding the evidence base each time.

The launch coincides with Wingsure’s participation in two major global coffee gatherings in Switzerland: the Global Coffee Platform’s 10th Anniversary Celebration in Geneva on September 30 and the Swiss Coffee Trade Association’s 17th Forum & Dinner in Montreux on October 1 – 2 – bringing industry leaders together around the future of coffee.

About Wingsure

Wingsure is a deep-tech agricultural intelligence company and an SRI spinout building verified farm-level intelligence for the global agriculture sector. The company uses computer vision, geospatial technologies, multilingual artificial intelligence, machine learning and guided, field-level digital capture to transform farm evidence into trusted, decision-grade intelligence.

With a presence across New York, Kolkata, Bogotá and Kuala Lumpur, Wingsure supports applications spanning sustainability, production, sourcing, compliance, regenerative agriculture, finance, insurance and risk management. Its technology enables farm-level information to be captured, verified and continuously enriched, helping enterprises make better-informed decisions while allowing growers to derive greater value from the records they help create.

For more information, please visit www.wingsure.co or email hello@wingsure.co.

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