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Valtora - Secure File Management System Using Blockchain, IPFS, and Smart Contracts

2025· article· W4416263579 on OpenAlex
Ayush Lokre, Samruddhi Faratkhane, Shagufta Bagwan-Sheikh

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal For Multidisciplinary Research · 2025
Typearticle
Language
FieldComputer Science
TopicAdvanced Data Storage Technologies
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsPermissionUploadFile systemPublic-key cryptographyData integrityMetadataDatabase transactionEncryptionCryptography

Abstract

fetched live from OpenAlex

In the contemporary digital landscape, traditional centralized file storage systems present significant vulnerabilities including single points of failure, unauthorized access, and lack of transparent audit mechanisms. This project presents a Decentralized Data Vault system that leverages blockchain technology, distributed storage, and cryptographic security to address these critical challenges. The system integrates IPFS (InterPlanetary File System) for decentralized content-addressed storage, Solana blockchain for immutable transaction logging, and MongoDB for metadata management. When users upload files, they are encrypted and stored on IPFS, generating unique content identifiers (CIDs). These CIDs, along with comprehensive metadata, are cryptographically logged on the Solana blockchain, creating an immutable audit trail ensuring data integrity and non-repudiation. A key innovation is the three-tier permission architecture (read, write, admin) enabling fine-grained access control. Users with read-only permissions can view files through secure browser-based viewers—PDFs rendered using PDF.js and Office documents converted to HTML using Mammoth—with comprehensive download prevention mechanisms including disabled right-click, copy protection, watermarking, and keyboard shortcut blocking. Write permission enables viewing and downloading, while admin permission grants complete file management capabilities. The frontend, built with React and TypeScript, provides an intuitive interface with drag-and-drop upload, real-time progress tracking, and responsive design. The Node.js/Express backend implements RESTful APIs with JWT-based authentication, malware scanning using ClamAV, and email notifications via Nodemailer. Security measures include multi-layer encryption, CORS policies, rate limiting, and comprehensive input validation. The blockchain integration provides immutable logging of all operations, transparent audit trails, and cryptographic proof of ownership. Advanced features include public link generation with expiration times, dynamic permission management, and intelligent file preview systems supporting multiple formats (PDF, DOCX, XLSX, PPTX, images, videos). Real-world applications span multiple industries: legal firms requiring tamper-proof document storage, healthcare organizations needing HIPAA-compliant secure sharing, research institutions protecting intellectual property, government agencies managing classified documents, and financial services securing sensitive information. This system represents a paradigm shift in secure file management, combining trustless blockchain properties, distributed storage resilience, and modern web technologies to create a solution that is simultaneously more secure, transparent, and user-friendly than traditional alternatives. By eliminating central server dependencies and implementing cryptographic verification, the Decentralized Data Vault establishes a scalable framework for next-generation digital collaboration where security, privacy, and user sovereignty are fundamental design principles.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.871
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0040.007
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.080
GPT teacher head0.431
Teacher spread0.352 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it