Press Release
WarRin Protocol: A point-to-point anonymous privacy communication system
Dr.WarRin
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.
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
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.
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.
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:
Curve25519 Curve Mathematical Expression:
Curve25519 encryption algorithms are 
Generate a one-time random secret 
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
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 
3.2 Allocation
WarRin protocol node distribution
3.2.1 Node allocation
Set the initial price 
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
3.2.2 Total number of address assignments
Each node occupies one address, and the total number of 
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 
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.
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.
ContractDataExtraction.com has launched a new AI-powered platform designed to convert contracts into structured, spreadsheet-ready data. The software is intended to help legal, procurement, and operations teams work more effectively with contract information that is often difficult to track once it is locked inside static documents.
United States, 1st Apr 2026 – ContractDataExtraction.com recently announced the launch of its new contract analysis platform, a software solution developed to help organizations extract structured data from contracts, agreements, and related records through AI.
The release addresses a common challenge in contract management. While contracts often contain critical information tied to renewal timing, payment obligations, termination rights, liability terms, and operational commitments, much of that information remains embedded in documents that are easy to store but difficult to monitor at scale. In many organizations, this leads to fragmented review processes, limited visibility across contract portfolios, and avoidable risk when key terms are not surfaced in time.
ContractDataExtraction.com was developed to address that gap by converting contract language into structured output that can be searched, filtered, and analyzed more easily. According to the company, the platform is designed to identify key provisions and business terms across a wide range of contract formats without requiring document-specific templates or manual setup. The software is intended to support both newly received contracts and legacy archives that may currently sit in shared folders, inboxes, or document repositories without a practical way to compare them at scale.
The company says the platform is especially relevant for teams that need contract data in a working format rather than a storage format. In legal and procurement environments, the challenge is often not access to contracts themselves, but the time required to locate and organize the information that matters across hundreds or thousands of files. ContractDataExtraction.com is positioning its platform around that operational need, with an emphasis on helping businesses turn agreements into usable datasets that support oversight, compliance, and planning.
The launch also reflects a broader shift in how organizations are approaching contract operations. As companies place greater emphasis on renewal management, vendor governance, and internal controls, there is increasing demand for tools that can surface contractual information without requiring line-by-line manual review for every document. The company says this is particularly important where large contract inventories make traditional tracking methods difficult to sustain.
ContractDataExtraction.com also states that the platform is SOC 2 Type 2 certified and HIPAA compliant, uses AES-256 encryption for data at rest, protects data in transit with TLS 1.2 or higher, does not use customer files to train AI models, and deletes processed contracts within 24 hours. According to the company, these measures are intended to support organizations that require stronger standards around privacy, security, and document handling.
One user described the impact by saying that a contract archive containing thousands of documents could be converted into a searchable spreadsheet within days, allowing the team to identify expiration dates and renewal terms that had previously been difficult to track. The company says this reflects growing demand for tools that can help organizations move from passive contract storage to more active contract visibility.
About ContractDataExtraction.com
https://www.contractdataextraction.com aims to help organizations extract structured data from contracts using AI. The platform is designed to make information from agreements, NDAs, leases, and other contract records easier to use in spreadsheets, reporting tools, and operational workflows.
Media Contact
Organization: ContractDataExtraction.com
Contact Person: Nora Kelly
Website: https://www.contractdataextraction.com/
Email: Send Email
Country:United States
Release id:43460
The post ContractDataExtraction.com Launches AI Tool to Convert Contracts into Structured Data appeared first on King Newswire. This content is provided by a third-party source.. King Newswire makes no warranties or representations in connection with it. King Newswire is a press release distribution agency and does not endorse or verify the claims made in this release. If you have any complaints or copyright concerns related to this article, please contact the company listed in the ‘Media Contact’ section
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.
Press Release
BankStatementScanningSoftware.com Launches AI Platform to Process Financial Statements
BankStatementScanningSoftware.com has launched a new AI-powered platform designed to extract transaction data from bank statements and other financial records into structured spreadsheet output. The software is intended to support accounting and finance teams that need a more efficient way to work with statement data across multiple institutions and formats.
United States, 1st Apr 2026 – BankStatementScanningSoftware.com announced the launch of its new cloud-based statement processing platform, a software solution developed to help businesses and accounting firms extract structured data from bank statements, credit card statements, brokerage records, and related financial documents.
The release is aimed at a longstanding operational challenge in accounting workflows. Financial statements often arrive in digital form, but the information they contain is not always easy to move into spreadsheets, reconciliation processes, or downstream accounting systems. When records come from multiple institutions and follow different layouts, the manual work involved in reviewing and keying transaction data can increase quickly, particularly during month-end close, client onboarding, and tax-season processing.
BankStatementScanningSoftware.com was developed to address that problem with software designed specifically for financial statement extraction. According to the company, the platform uses AI to read statement layouts from a wide range of institutions and convert transaction information into structured output without requiring per-bank templates or local desktop installation. The software is intended to support cloud-based workflows where teams need to process varied statement formats at volume while maintaining a consistent output for review and import.
The company says the platform is especially relevant for firms that manage records across many client accounts or financial institutions at the same time. In those settings, the issue is not simply reading a statement but standardizing the information inside it so it can be used for categorization, reconciliation, and reporting. BankStatementScanningSoftware.com is positioning its software around that need, with an emphasis on helping teams reduce the operational burden of statement handling rather than treating extraction as a standalone OCR task.
The platform also includes support for batch processing, connected intake, and API-based workflows, which the company says reflects broader changes in how accounting teams are approaching automation. As more firms move away from desktop tools toward shared cloud systems, there is growing interest in software that can fit into larger financial processing pipelines without introducing additional formatting work or manual cleanup at the point of intake.
BankStatementScanningSoftware.com also states that the platform is SOC 2 Type 2 certified and HIPAA compliant, uses AES-256 encryption for data at rest, protects data in transit with TLS 1.2 or higher, does not use customer files to train AI models, and deletes processed statements within 24 hours. According to the company, these measures are intended to support organizations that require stronger controls around privacy, security, and financial data handling.
One user described the effect by saying that a statement-processing workflow spanning multiple clients, institutions, and account types could be reduced substantially after moving from desktop OCR software to a cloud-based extraction model. The company says this reflects growing demand for tools that can help finance teams handle statement variation more efficiently while improving throughput during high-volume periods.
About BankStatementScanningSoftware.com
https://www.bankstatementscanningsoftware.com aims to help businesses and accounting teams extract structured transaction data from financial statements using AI. The platform is designed to support cloud-based accounting workflows by making bank, credit card, brokerage, and related statement data easier to use in spreadsheets and downstream systems.
Media Contact
Organization: BankStatementScanningSoftware.com
Contact Person: Ryan Cooper
Website: https://www.bankstatementscanningsoftware.com/
Email: Send Email
Country:United States
Release id:43459
The post BankStatementScanningSoftware.com Launches AI Platform to Process Financial Statements appeared first on King Newswire. This content is provided by a third-party source.. King Newswire makes no warranties or representations in connection with it. King Newswire is a press release distribution agency and does not endorse or verify the claims made in this release. If you have any complaints or copyright concerns related to this article, please contact the company listed in the ‘Media Contact’ section
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.
PDFtoQBO.co has launched a new AI-powered platform designed to convert PDF bank statements into QBO files for QuickBooks import. The software is intended to help bookkeepers, accountants, and finance teams reduce the manual work involved in transferring bank transaction data from statements into accounting systems.
Oklahoma, United States, 1st Apr 2026 – https://www.pdftoqbo.co announced the launch of its new bank statement conversion platform, a software solution developed to help businesses convert PDF bank statements into QBO files compatible with QuickBooks.
The release addresses a recurring challenge in bookkeeping and financial recordkeeping. Although bank statements are often available in digital form, they are not always delivered in a format that can be imported directly into accounting software. When QBO files are unavailable from a financial institution, firms may still need to enter transaction data by hand or rely on workarounds that add time to reconciliation and monthly close processes.
PDFtoQBO.co was developed to address that gap by converting statement data into a format designed specifically for QuickBooks import. According to the company, the platform uses AI to extract transaction details from PDF bank statements and map them into QBO-compatible output without requiring bank-specific templates or manual setup. The software is intended to work across varying statement layouts, allowing accounting teams to process records from different institutions through the same workflow.
The company says the platform is especially relevant for bookkeeping firms and finance teams that manage statements from multiple banks and need a more reliable way to move historical or ongoing transaction data into QuickBooks. In those settings, the issue is often less about access to statements than about the amount of manual work required to make them usable in the accounting system. PDFtoQBO.co is positioning its platform around that practical need, with a focus on helping teams shorten the path from statement receipt to system-ready import.
The launch also reflects a broader shift in accounting operations toward reducing manual processing around source documents. As firms seek to improve efficiency without changing how records are received from financial institutions, tools that can translate static statements into import-ready formats are becoming more relevant. The company says this is particularly important for workflows involving cleanup projects, client onboarding, and recurring bookkeeping tasks where transaction entry can otherwise consume significant staff time.
PDFtoQBO.co also states that the platform is SOC 2 Type 2 certified and HIPAA compliant, uses AES-256 encryption for data at rest, protects data in transit with TLS 1.2 or higher, does not use customer documents to train AI models, and deletes processed files within 24 hours. According to the company, these measures are intended to support organizations that require stronger privacy and security standards when handling sensitive financial records.
One user described the impact by saying that a process which had previously required most of a workday per client could be reduced to minutes when converting a full year of PDF bank statements into QBO files. The company says this reflects growing demand for tools that can reduce manual transaction entry while fitting more directly into QuickBooks-based workflows.
About PDFtoQBO.co
PDFtoQBO.co is a platform that helps businesses convert PDF bank statements into QBO files for QuickBooks using AI. The platform is designed to make transaction data from bank statements easier to import into accounting workflows with less manual effort.
Media Contact
Organization: PDFtoQBO.co
Contact Person: Chloe Perry
Website: https://www.pdftoqbo.co/
Email: Send Email
State: Oklahoma
Country:United States
Release id:43458
The post PDFtoQBO.co Launches AI Platform for PDF Bank Statement Conversion to QBO appeared first on King Newswire. This content is provided by a third-party source.. King Newswire makes no warranties or representations in connection with it. King Newswire is a press release distribution agency and does not endorse or verify the claims made in this release. If you have any complaints or copyright concerns related to this article, please contact the company listed in the ‘Media Contact’ section
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.
ContractDataExtraction.com Launches AI Tool to Convert Contracts into Structured Data
BankStatementScanningSoftware.com Launches AI Platform to Process Financial Statements
PDFtoQBO.co Launches AI Platform for PDF Bank Statement Conversion to QBO
Benzinga Money Article Discusses How to Become Part of the 12% of Retirees Who Have Achieved the Recommended $550,000 Minimum Retirement Savings Threshold
Apu Apustaja Conquers New York with Lively Street Ads, Including Times Square Billboard
Bay Smokes Maintains Quality Amid Legislative Changes in the Hemp Industry
-
Press Release5 days ago
Post Oak Group Advises on Successful Divestiture of Magnify Equity’s Property Management Platform
-
Press Release5 days ago
CGTN: How Boao Forum for Asia fosters shared development in Asia and beyond
-
Press Release1 week ago
JGCMGS Launches Real-Time Proof of Reserves System
-
Press Release1 week ago
IRS Announces Updated FEIE Limit for 2026, Nationly Updates Resources
-
Press Release4 days ago
Asprofin Bank Funds Construction of Qatari Royal Family Nanocenter to Transform AI Infrastructure
-
Press Release5 days ago
Travel as Education: Lauren Nash on What the World Teaches When You Show Up Prepared
-
Press Release4 days ago
Atlas Designs Celebrates 500+ Five-Star Projects with Spring Savings on Permit Services
-
Press Release4 days ago
IAC to Represent Kazakhstan at Paris Arbitration Week 2026