Intellectual Property Protection Through Blockchain: Introducing the Novel SmartRegistry-IP for Secure Digital Ownership

Abstract

The rise of digital content has made the need for reliable and practical intellectual property (IP) management systems more critical than ever. Most traditional IP systems are prone to issues such as delays, inefficiency, and data security breaches. This paper introduces SmartRegistry-IP, a system developed to simplify the registration, licensing, and transfer of intellectual property assets in a secure and scalable decentralized environment. By utilizing the InterPlanetary File System (IPFS) for decentralized storage, SmartRegistry-IP achieves a low storage latency of 300 milliseconds, outperforming both cloud storage (500 ms) and local storage (700 ms). The system also supports a high transaction throughput of 120 transactions per second. Through the use of smart contracts, licensing agreements are automatically and securely enforced, reducing the need for intermediaries and lowering operational costs. Additionally, the proof-of-work process verifies all transactions, ensuring higher security and maintaining data consistency. The platform integrates an intuitive graphical user interface that enables seamless asset uploads, license management, and analytics visualization in real time. SmartRegistry-IP demonstrates superior efficiency compared to traditional systems, achieving a blockchain delay of 300 ms, which is half the latency of standard systems, averaging 600 ms. According to this study, adopting SmartRegistry-IP provides IP organizations with enhanced security and transparent management, ensuring they can overcome operational challenges regardless of their size. As a result, the use of blockchain for intellectual property management is expected to increase, helping maintain precise records and reducing time spent on online copyright registration.

1. Introduction

The exponential growth of digital content has exposed critical vulnerabilities in traditional intellectual property (IP) management systems, which remain centralized, opaque, and inefficient [1,2,3]. These systems typically require 3–5 days for registration, lack transparent ownership verification, and incur high intermediary costs [4,5,6]. Blockchain technology offers a promising solution through its immutable ledger and smart contract capabilities [7,8,9,10], yet current implementations struggle with scalability when storing large digital assets directly on-chain [11,12,13,14]. This paper presents SmartRegistry-IP, a hybrid blockchain–IPFS framework that addresses these limitations by combining on-chain metadata management with decentralized off-chain storage [15,16,17,18,19]. Our system achieves 120 transactions per second (TPS) throughput and 300 ms storage latency, significantly outperforming existing solutions [20,21,22,23]. The main contributions of this work are (i) a modular architecture integrating blockchain and IPFS for scalable IP management, (ii) mathematical optimization models for storage and smart contract efficiency, (iii) comprehensive empirical validation demonstrating superior performance over current systems, and (iv) a production-ready implementation with an intuitive graphical interface. This research is motivated by the growing need for robust intellectual property protection in the digital era. SmartRegistry-IP is presented as a secure framework, but its primary contribution lies in protecting ownership rights, preventing IP theft, and providing transparent, verifiable asset management.

Unlike prior approaches, SmartRegistry-IP integrates real-time analytics, an intuitive GUI, and mathematical optimization models that fine-tune both decentralized storage placement and smart contract execution. The result is a secure, transparent, and practical environment for managing digital IP at scale.

This paper addresses the following objectives:

• Design and implement SmartRegistry-IP, a modular system that couples smart contracts with IPFS-based storage to register, license, and audit digital assets.
• Formulate two mathematical optimization models that (i) minimize storage cost/latency trade-offs and (ii) reduce smart contract execution overhead, explicitly linking each model to concrete system components.
• Define a structured validation plan with clearly stated research questions, datasets, benchmarks, and metrics (latency, cost, and scalability).
• Empirically evaluate SmartRegistry-IP against two baseline datasets/systems, reporting quantitative improvements and discussing limitations.

• Research Questions:

To comprehensively evaluate the effectiveness of SmartRegistry-IP in intellectual property protection, this study answers the following research questions:

• RQ1: Does SmartRegistry-IP improve digital intellectual property protection compared to baseline systems?
• RQ2: Does the framework ensure tamper-proof ownership verification and authenticity of IP assets using blockchain technology?
• RQ3: Is decentralized IP storage via IPFS more secure, cost-efficient, and reliable than traditional centralized alternatives?
• RQ4: Does the use of optimized smart contracts enhance the speed, safety, and automation of IP licensing and transfers?

• Research Motivation and Scope:

SmartRegistry-IP introduces a hybrid blockchain–IPFS framework focused on tackling the challenges of intellectual property protection in the digital era [24,25,26,27,28]. It secures ownership and management of digital assets by using blockchain for verifiable on-chain records and smart contracts for automated licensing [29,30,31,32], reducing intermediaries and delays [11,33,34,35]. With IPFS integration, the system improves storage reliability, scalability, and retrieval speed, ensuring intellectual property assets remain accessible, protected, and efficiently managed across digital environments [36,37,38].

• Research Strategy:

The proposed work follows a structured research strategy aimed at addressing the growing challenges in intellectual property protection. Digital IP faces increasing threats related to security, scalability, and transparent ownership verification, which traditional centralized systems fail to manage effectively. Existing blockchain-based frameworks, although promising, still suffer from high latency, limited scalability, and poor integration with decentralized storage. To overcome these limitations, this study proposes SmartRegistry-IP, a hybrid framework that integrates blockchain, IPFS, and smart contracts to ensure secure, efficient, and scalable IP management. The effectiveness of the proposed solution is validated using three benchmark datasets; its performance is evaluated in terms of transaction throughput, latency, storage cost efficiency, and security indicators, demonstrating its potential to transform digital IP protection.

Section 2 outlines the necessary background and related work. Section 3 presents the system architecture and workflow. Section 4 details the mathematical formulations and their linkage to system-designed modules. Section 5 demonstrates the system implementation details. Section 6 outlines the validation methodology. Section 7 discusses the results and findings. Section 8 concludes this paper and proposes future work.

2. Related Work

Traditional methods for protecting IP often fall short in the digital age, prompting researchers to explore blockchain technology as a promising alternative. Blockchain enhances the speed, cost efficiency, and reliability of protecting creative works and inventions across their life cycles [6], primarily due to its immutable nature, which ensures verifiable ownership and facilitates international IP dispute resolution [7]. Foundational studies have clarified specific areas where blockchain can reinforce existing IP systems [8], ranging from 3D printing confidentiality [9] to broader IP classifications [10]. The technology’s robust security features prove particularly valuable in competitive and innovation-driven sectors [11], including healthcare, where blockchain helps safeguard biotechnology IP [12].

As blockchain adoption grows, legal and policy analyses have highlighted the need for harmonized frameworks to manage blockchain-based IP and tokenized assets [13,14,15]. Building on these foundations, researchers have proposed innovative applications across various domains. In the manufacturing sector, studies have explored combining blockchain with IoT for adaptive digital manufacturing IP systems [16] and addressed authentication frameworks for IoT networks [36], with specific criteria established for adapting blockchain consensus algorithms to IoT-specific requirements [38]. The 3D printing industry has received particular attention, with frameworks addressing IP confidentiality [9], supply chain protection [11,33], and the “digital copycat dilemma” that emerges from increasingly digitized manufacturing [37].

Smart contracts have emerged as a key enabler for autonomous IP management [17], automating licensing processes through rule-based functions such as access control and royalty payments, thereby reducing administrative costs and ensuring compliance [28,29]. Some frameworks propose combining blockchain with artificial intelligence to streamline tasks like patent filing and license management [30], while others focus on regulatory-compliant smart contracts for legal automation [31,32]. Practical implementations have demonstrated blockchain’s effectiveness in copyright protection [18,19], digital art ownership via NFTs [20], and national IP law enforcement [21], with emerging cross-chain models offering enhanced interoperability for future systems [22,23].

The integration of IPFS with blockchain has been proposed to address the scalability challenges of storing large volumes of IP data [24], reflecting a broader trend of technological and legal advancements contributing to more robust blockchain-based IP protection systems. By combining blockchain with IPFS, systems can store essential metadata on-chain while offloading large digital assets to decentralized storage, achieving both security and scalability. Recent advances have also addressed critical security and privacy challenges, including the development of zero-trust blockchain frameworks that enhance protection for confidential information while maintaining system usability [34], and optimized consensus mechanisms specifically tailored for intellectual property transaction scenarios [35].

Despite ongoing legal concerns—such as jurisdictional inconsistencies and regulatory gaps—recent studies affirm blockchain’s potential as a foundational infrastructure for future IP governance. Its decentralization, immutability [26], and transparency ensure secure, real-time ownership validation. Once data is recorded, it becomes unalterable, providing a reliable record of authorship and usage [27]. This is especially vital in digital ecosystems where IP theft is prevalent.

Table 1. Comparative analysis of IP protection studies.

Attribute	Lin et al. (2020) [16]	Chan et al. (2023) [9]	Mishra et al. (2024) [20]	Ruhtiani (2023) [21]
Focus Area	Integration of blockchain with IoT for IP protection	Authentication and security for 3D-printed IP	Digital art ownership using blockchain and NFTs	Legal IP protection framework for digital copyright
Technology Used	Blockchain, IoT	Blockchain, smart contracts	Blockchain, NFTs	Blockchain, IPFS
Key Findings	Demonstrated automated IP monitoring and compliance enforcement through IoT integration	Proposed a framework for secure 3D printing IP transactions, reducing risks of unauthorized access	Enhanced security for digital art ownership via NFT-based traceability and ownership verification	Showed blockchain’s effectiveness in secure, verifiable copyright records, reducing infringement
Limitations	Limited scalability for high data volumes and real-time processing	High costs due to gas fees and technical barriers for smaller businesses	Limited to digital art, lacks generalizability across other IP domains	Lack of a comprehensive storage solution for large digital files, limited to legal use cases
Research Methodology	Simulation-based architecture design	Conceptual framework and case analysis	Theoretical framework with NFT application examples	Legal framework analysis and case study on digital copyright
Applications	IoT-based IP protection across digital manufacturing sectors	Secure IP authentication for the 3D printing industry	NFT-based digital ownership and transfer for digital art	Copyright registration and verification for digital media
Performance Metrics	Not specified	Seventy TPS throughput reported	Not applicable (theoretical)	Thirty TPS throughput reported
Storage Solutions	Local storage with IoT devices	Cloud-based storage	On-chain NFT metadata	IPFS for decentralized storage

provides a comparative summary of key recent studies that best represent the technological approaches most relevant to blockchain-based IP management systems.

In addition to the four studies summarized in Table 1, we conducted a comprehensive review of 23 recent works (2020–2025) that address blockchain-enabled intellectual property protection. These studies explore various domains, including decentralized licensing systems [16], NFT-based digital ownership frameworks [20], and IPFS-driven distributed storage models [21]. The four studies presented in Table 1 were specifically selected because they best represent the technological relevance to SmartRegistry-IP, focusing on blockchain and IPFS integration for intellectual property management. Furthermore, they were chosen for their relevance, as all were published between 2020 and 2024, ensuring the inclusion of the most recent advancements in the field. Another reason for selecting these studies is their diversity, as they cover a broad range of contexts, such as IoT-based IP protection, 3D printing authentication, NFT-based digital ownership, and legal frameworks for copyright enforcement. Finally, the selected studies provide direct comparability since they report measurable performance metrics—such as throughput, latency, and security—that can be benchmarked against SmartRegistry-IP, enabling a more accurate and meaningful evaluation.

Problem Statement: Blockchain holds significant promise for securing IP through immutable, transparent ledgers and automated workflows. However, current solutions remain fragmented and narrowly scoped, often tailored to sectors, such as digital art or 3D printing, while neglecting the full spectrum of digital assets. Although some platforms pair smart contracts with decentralized storage (e.g., IPFS), they struggle with high costs, inconsistent cross-platform compatibility, limited scalability, and uncertain regulatory compliance. This fragmentation creates barriers, particularly for small and medium-sized enterprises (SMEs), which face complexity and expense when adopting blockchain-based IP tools. Moreover, most systems tackle either ownership verification or off-chain storage in isolation, lacking an end-to-end framework that unifies automation, real-time performance, and legal traceability.

To close these gaps, we introduce SmartRegistry-IP, a comprehensive IP management platform that enables the following:

• Integration of IPFS-backed storage for cost-effective, scalable asset hosting.
• Automation of licensing and transfers via smart contracts calibrated for high throughput.
• Real-time analytics and verifiable audit logs through an intuitive GUI.
• Maintenance of compliance readiness by recording all events on-chain under standardized schemas.

By unifying these components into a single architecture, SmartRegistry-IP delivers full lifecycle management: registration, licensing, distribution, and auditing, for digital assets of any type or scale, thereby advancing blockchain-IP implementations toward practical, high-performance adoption.

3. SmartRegistry-IP: System Overview

To solve the problem introduced in Section 2, we designed a blockchain-based platform that allows IP owners to safely, transparently, and efficiently manage their assets. By combining a permissioned blockchain for metadata and licensing logic, IPFS for scalable off-chain storage, smart contracts for automated workflows, and proof-of-work for transaction integrity, the system delivers transparency, efficiency, and resilience.

In this section, we present the details of the key functionalities, workflow, and architecture of the SmartRegistry-IP system.

3.1. Key Functionalities

Table 2. SmartRegistry-IP functionalities.

Functionality	Description
User Registration	Securely registers new users and assigns unique identifiers stored on the blockchain.
Asset Upload	Allows users to upload intellectual property assets, storing metadata on the blockchain.
License Management	Automates the creation and management of licenses using smart contracts.
Decentralized Storage	It utilizes IPFS to securely store large files, linking file hashes to the blockchain.
Audit Logs	Provides immutable logs of all user and system activities for accountability and transparency.
Analytics Dashboard	Displays system performance metrics, including uploads, licenses, and transactions.
Security Systems	Ensures data and user authentication security through encryption and secure hashing.
System Administration	Enables administrators to manage system configurations and oversee operations.

summarizes the core functionalities of SmartRegistry-IP and explains how each contributes to secure, efficient, and scalable intellectual property (IP) protection. These functionalities collectively ensure transparent ownership verification, automated licensing, decentralized storage, and real-time monitoring of IP assets.

3.2. System Architecture

The architecture supports reliable data exchange between modules. The diagram in Figure 1 expands on the architecture by outlining each main element and its interactions with the others.

Several main modules make up the SmartRegistry-IP platform:

• User Registration Block: Handles user authentication and registration. Upon registration, users receive a unique, secure on-chain identifier.
• Asset Upload Block: This feature enables users to incorporate patents, trademarks, and copyrights into the system. All uploaded files are processed for attachment to the blockchain, and information is saved to track their origin. Some commonly supported file types are PDF, Word documents, and plain text files.
• Blockchain Ledger Block: It is responsible for most actions in the system, ensuring that registration, license issuance, and changes to blockchain ownership occur smoothly and securely. With proof-of-work, every transaction is secure and immutable once it is completed.
• Smart Contracts Block: It enables the management of tasks such as IP licenses and transferring ownership of files or patents, all without requiring manual intervention. Smart contracts eliminate the need for intermediaries and ensure that the rules established for a deal are adhered to.
• Proof-of-Work Block: Using consensus, transactions are validated as they appear on the blockchain. This ensures that data cannot be altered without proper authorization.
• Decentralized Storage Block (IPFS Block): Relies on the InterPlanetary File System (IPFS) to keep large intellectual property files safe and secure. The blockchain enables efficient access to and verification of metadata and file hashes.
• License Management Block: Enables users to set up, control, and follow their intellectual property licenses. This block relies on smart contracts to allow for smooth and automatic license management.
• Analytics Block: Displays details about how the system is working, including the number of files uploaded, the number of license requests made, and the number of transactions processed. Insights are presented using graphs that help managers track the system’s performance.
• System Admin Block: Facilitates system configuration and management. Administrators can monitor user activity, manage network resources, and adjust system settings as needed.
• Security Systems Block: Ensures that data remains safe and protects user information by utilizing features such as password encryption and data hashing, as well as controlling access to specific types of information.

SmartRegistry-IP combines the tamper-proof guarantees of blockchain with the elastic capacity of IPFS to deliver a unified IP management platform that is simultaneously immutable, highly scalable, and secure. By offloading large files to decentralized storage, it handles growing user bases and massive data volumes without performance bottlenecks. At the same time, smart contracts automate registration, licensing, and transfers—eliminating manual errors and accelerating workflows. Every action is logged in real time on-chain and in audit trails, offering end-to-end transparency and legal traceability, and advanced encryption, secure hashing, and proof-of-work consensus safeguard data integrity and access control. All of this is wrapped in an intuitive GUI, making the system accessible to creators, licensees, and administrators alike and addressing gaps in traditional IP systems with a high-performance, user-friendly solution for the digital era.

3.3. System Workflow

The SmartRegistry-IP workflow orchestrates modular blocks to secure and deliver IP assets end-to-end. The workflow is depicted in Figure 2, and can be summarized as follows:

• User Registration Block.

Asset Preparation (Data Owner): The user registers and receives a Decentralized Identifier (DID). They then hash and encrypt their IP file locally.

2.

Asset Upload Block.

On-Chain Registration and Off-Chain Storage: The metadata hash and DID are recorded on the Blockchain Ledger block, establishing a tamper-proof ownership record. At the same time, the encrypted file is pinned to the decentralized storage (IPFS) block, ensuring distributed redundancy.

3.

License Management Block.

Access Request: A Data Requester retrieves the encrypted file from IPFS and sends an access request via the smart contract. The License Management module assesses the request based on pre-defined rules.

4.

Proof-of-Work (PoW) Block.

Authorization and Validation: Transactions pass through PoW consensus. The smart contract verifies ownership and enforces a multiparty authentication step, such as multisignature or zero-knowledge proofs, before granting access.

5.

Audit Log Block.

End-to-End Security and Transparency: Every action (hash submission, upload, request, grant) is immutably recorded on-chain and mirrored in off-chain logs, providing a complete, auditable history.

6.

Analytics Block.

Processes audit streams and performance metrics to generate real-time dashboards, helping users and administrators monitor throughput, latency, and system health.

7.

System Admin Block

Manages configuration, oversees node replication and consensus settings, and maintains platform reliability.

Figure 2 illustrates the complete workflow of the proposed SmartRegistry-IP system for secure intellectual property (IP) protection. The process starts with the data owner preparing the IP file, which is hashed and encrypted locally to ensure confidentiality. After encryption, two operations occur in parallel: the metadata hash is submitted to the blockchain network for immutable ownership verification, and the encrypted IP file is stored in the IPFS decentralized storage system. Once the encrypted file reference is available, a data requester retrieves it from IPFS and sends an access request via the smart contract, while the blockchain sequentially verifies ownership. The smart contract then validates the request through multiparty authentication mechanisms, such as multisignature or zero-knowledge proofs, ensuring that only authorized users gain access. Upon successful validation, access is granted, the data is decrypted, and the authorized IP content is delivered securely. This explanation clarifies which tasks occur sequentially and which are executed in parallel, providing a clearer understanding of the overall system workflow.

4. Mathematical Models for Design Optimization

Building on the system overview in Section 3, we formalize two optimization models to enhance key components: (i) a storage optimization model that balances replication redundancy and node placement to minimize cost versus retrieval latency in the Decentralized Storage Block and (ii) a contract optimization model that reduces smart contract execution overhead while preserving on-chain integrity. Each model is presented with clear notation, objectives, constraints, and explicit linkage to its corresponding system module, ensuring that theoretical improvements translate directly into practical performance gains. By embedding these models into their respective modules, we ensure that SmartRegistry-IP not only remains secure and transparent but also delivers the fast, scalable, and cost-effective performance that digital IP management demands.

4.1. Blockchain Storage Optimization for IP Metadata

In blockchain-based IP systems, the efficient storage and retrieval of IP metadata is critical for ensuring performance, scalability, and data integrity. While blockchain offers immutability and traceability, it is not well suited for storing large amounts of data directly due to high costs and latency. Therefore, off-chain storage systems, such as the InterPlanetary File System (IPFS), are employed, with the blockchain storing metadata and content hashes. This section introduces an optimization model that balances storage cost, retrieval speed, and redundancy in a blockchain–IPFS hybrid architecture for IP metadata management.

• Problem Definition:

As the number and size of IP assets grow, naive replication across IPFS nodes leads to excessive storage fees and longer retrieval times. This model dynamically selects the number of replicas and their node locations to strike the best trade-off between cost and latency. This guarantees rapid metadata access even under heavy load while keeping decentralized storage expenses under control.

• Parameters and Decision Variables:

Let there be a set of metadata records m ∈ M, where each record contains descriptive data about IP asset i (e.g., title, author, hash pointer, license terms).

• Parameters:
• $S_i$: Storage cost for asset i.
  $T_i$: Retrieval time for asset i.
• $R_i$: Redundancy level for each file.
• $\beta , \delta$: Scaling constants for cost and time, respectively.
• $\lambda$: Regularization parameter for redundancy penalty.
• $R_{\mathit{min}x}$: Minimum required redundancy threshold.
• $\eta$: Blockchain node storage efficiency.
• $\left|M_i\right|$: The count of asset i redundant files.

The storage cost $S_i$ and retrieval time $T_i$ are functions of the metadata size. They are expressed as follows:

$$S_i= \beta ·{\displaystyle \frac{\left|M_i\right|}{\eta }},$$

(1)

$$T_i=\delta · {\displaystyle \frac{\left|M_i\right|}{\eta }}.$$

(2)

• Objective Function:

The optimization model is directly aligned with the goal of intellectual property protection rather than being a separate objective. In SmartRegistry-IP, minimizing the combined cost–time efficiency function ensures that intellectual property assets are registered, verified, and accessed quickly, which is essential for preventing unauthorized use or duplication. Lower retrieval latency enables faster ownership validation, while reducing storage costs supports the scalability of decentralized IP protection across large datasets. The inclusion of redundancy constraints guarantees that all intellectual property files remain secure, reliably stored, and available in distributed IPFS nodes, even under network failures. Thus, this optimization is not intended merely for performance improvement but is a core enabler of robust, real-time intellectual property protection in SmartRegistry-IP.

The optimization objective, shown in Equation (3), minimizes the combined cost–time efficiency function while ensuring redundancy requirements.

$$\mathit{min}\sum _{i=1}^n{\displaystyle \frac{S_i}{T_i}}+\lambda \sum _{i=1}^n{\left(R_i-R_{min}\right)}^2,$$

(3)

where $\lambda$ is a regularization parameter that penalizes deviations from the minimum redundancy threshold $R_{\mathit{min}x}$.

The model is subject to the following constraints:

$$\sum _{i=1}^n{S}_i\le C,$$

(4)

$$R_i\ge R_{min}, \forall i \in \left\{1, \dots , n\right\},$$

(5)

$$T_i\le T_{max}, \forall i \in \left\{1, \dots , n\right\}.$$

(6)

• System Linkage:

This model configures the Decentralized Storage Block by managing how metadata is stored across decentralized IPFS nodes. It helps reduce storage cost and retrieval time while ensuring that critical data has the necessary redundancy. SmartRegistry-IP’s storage efficiency is discussed in Section 7.2.

4.2. Smart Contract Optimization for IP Licensing and Transfer

Optimizing the smart contract layer is critical for balancing gas costs, execution speed, and legal compliance in automated IP licensing and transfer. In SmartRegistry-IP, a formal execution cost model governs which contract functions to invoke and in what sequence—minimizing cumulative gas fees and processing delays while enforcing licensing rules and regulatory constraints. By autonomously selecting the most efficient execution path for each licensing event, the model reduces administrative overhead and preserves on-chain integrity.

Inefficient contract designs can otherwise inflate transaction fees, slow workflows, or even breach licensing agreements. Prior work underscores these benefits: Alqarni [30] emphasizes that smart contracts enhance licensing efficiency and auditability in decentralized ecosystems. Holland et al. [33] confirm its applicability in product lifecycle IP scenarios, while Alketbi and Mahmuddin [26] show practical deployment in blockchain-enabled IP workflows.

• Problem Definition:

Every licensing or transfer operation consumes Ethereum gas and incurs execution delays. Without optimization, frequent or complex contract calls can drive up transaction fees and create bottlenecks. This model chooses which smart contract functions to invoke and in what sequence, subject to legal compliance constraints and latency bounds, to minimize gas usage and processing time. The result is a contract layer that scales to high transaction volumes without sacrificing on-chain integrity or regulatory adherence.

• Variables and Parameters:

Consider a smart contract with p functions, where each function $F_k$ is associated with the following parameters:

• $G_k$: Gas cost for function k.
• $T_k$: Execution time for function k.
• $\lambda$: Penalty coefficient for non-compliance.
• $\gamma$: Blockchain efficiency factor.
• $\alpha ,\phi$: Gas and time scaling constants, respectively.
• $\mu$: Penalty factor [35].
• $O_k$: Number of operations in function $F_k$.
• $L_k$: Licensing compliance (binary variable).

Let the binary variable $L_k$ represent licensing compliance for function $k$:

$$L_k=\left\{\begin{array}{c} 1, \\ 0,\end{array}\right.\begin{array}{c} if function complies with licensing terms,\\ otherwise.\end{array}$$

(7)

The gas cost and execution time are functions of the number of operations $O_k$ and the blockchain efficiency factor $\gamma$:

$$G_k= \alpha ·{\displaystyle \frac{O_k}{\gamma }},$$

(8)

$$T_k=\phi ·{\displaystyle \frac{O_k}{\gamma }}.$$

(9)

• Objective Function:

The objective is to minimize the total operational cost O by combining gas usage, execution latency, and penalties for license non-compliance:

$$min \sum _{k=1}^p(G_k+T_k)+\mu ·\sum _{k=1}^p{\left(1 - L_k\right)}^2,$$

(10)

where μ is a penalty factor for non-compliance.

The model is subject to the following constraints:

$$G_k\le G_{max}, \forall k \in \left\{1, \dots , p\right\},$$

(11)

$$\phi ·{\displaystyle \frac{O_k}{\gamma }} \le T_{max}, \forall k \in \left\{1,\dots , p\right\},$$

(12)

$$L_k\ge L_{min}, \forall k \in \left\{1, \dots , p\right\}.$$

(13)

This model ensures that smart contracts are optimized to be both cost-effective and fast while also being legally compliant. By tuning the constants α, β, and λ, system designers can prioritize performance, cost, or regulatory adherence based on the deployment context.

• System Linkage:

This model governs the smart contract layer, informing how registration and licensing functions are modularized to meet performance targets. The outcome is that smart contracts use gas more efficiently, transactions are completed more quickly, and licenses are honored. SmartRegistry-IP’s performance results are discussed in Section 7.1.

5. SmartRegistry-IP Implementation and Prototype

Building on the system overview and architecture defined in Section 3 and the optimization models formulated in Section 4, in this section, we develop a SmartRegistry-IP functional prototype that integrates a permissioned blockchain, IPFS-based storage, and an intuitive GUI. We detail the system architecture, the security and identity mechanisms, the prototype’s implementation, and the enhancements for rich metadata queries.

5.1. System Architecture and Interface

In Section 3.2, we presented the architecture design of SmartRegistry-IP’s modular blocks; here, we implement that design in a layered architecture, allocating each block to a distinct layer:

• Client/API and GUI Layer: A Python 3.10 software with a static sidebar for navigation and dynamic content panes (Home, Upload Asset, Manage Licenses, Analytics). This layer embodies the User Registration, Asset Upload, and Analytics blocks.
• Smart Contract Layer: Ethereum-compatible contracts encode the license management, dispute resolution, and proof-of-work logic, automatically enforcing registration and licensing workflows.
• Decentralized Storage Layer: IPFS clusters serve the Decentralized Storage block, storing large asset payloads off-chain and linking them to on-chain metadata for the Blockchain Ledger block.
• Monitoring and Analytics Layer: Backend services aggregate on-chain events and IPFS logs into a time-series database, powering the Analytics dashboard and the Audit Log block.
• Administration Layer: A role-based console supports the System Admin block, enabling configuration, resource allocation, and health monitoring.

5.2. Security and Decentralized Identity

SmartRegistry-IP enforces data integrity and accountability through the following:

• Immutable Ledger: All critical actions, such as registrations and license changes, are logged on-chain to prevent tampering.
• Smart Contracts: Embed business and licensing rules without manual intermediaries.
• Proof-of-Work Verification: Validates transactions and blocks unauthorized updates.
• Audit Logs: Provide a complete event history accessible in the Analytics panel.
• W3C-Compliant DIDs: Each asset is assigned a Decentralized Identifier document on-chain, embedding metadata, licensing policies, and cryptographic proofs. Owners manage rights via verifiable credentials, enabling Web 3.0-style control.

5.3. Prototype Implementation and Query Enhancement

In the prototype, we consider the following technical details:

• Front End (GUI): The SmartRegistry-IP GUI class initializes the window, constructs sidebar buttons, and dynamically renders content using Tkinter. The GUI layout is depicted in Figure 3.
• Back-End Services: Python scripts use ipfshttpclient for file operations and web3.py for smart contract interactions. Configuration files (node endpoints, gas settings, replication factors) enable easy customization.
• Rich Metadata Queries (TELEX): We integrated the TELEX-learned index within a trusted enclave (e.g., Intel SGX) to support sub-logarithmic queries on metadata fields (owner, category, timestamp) while preserving confidentiality.

6. Validation Methodology

In this section, we explain how SmartRegistry-IP will be empirically validated by linking each research question (RQ) to the optimization models in Section 4. The storage cost/latency model (Section 4.1) informs RQ3 by analyzing how decentralized placement affects efficiency and reliability. The smart contract gas/latency model (Section 4.2) underpins RQ1 and RQ2 by shaping execution strategies that minimize gas use and delays. Together, these models provide a framework to systematically measure the benefits of optimization-driven design.

6.1. Evaluation Dimensions and Analysis Overview

To evaluate the effectiveness and performance of SmartRegistry-IP, four core evaluation dimensions were analyzed.

• Dimension 1—Registration and Licensing Efficiency: Evaluates the time required for asset registration and license generation to ensure optimized intellectual property workflows.
• Dimension 2—Throughput and Latency: Measures system scalability by analyzing transactions per second and response delays under varying network loads.
• Dimension 3—Storage Cost and Reliability: Compares decentralized IPFS storage performance with traditional centralized solutions to assess cost efficiency and accessibility.
• Dimension 4—Security Performance: Examines access control mechanisms, encryption times, and data integrity to validate the robustness of intellectual property protection.

These evaluation dimensions are directly linked to the system’s objectives and correspond to the original research goals:

• System Efficiency: Addressed by registration/licensing time and throughput/latency to assess workflow optimization.
• Smart Contract Optimization: Evaluated based on throughput, latency, and security to measure execution speed and data integrity.
• Decentralized Storage Benefits: Assessed using storage cost, reliability, and latency comparisons across IPFS, cloud, and local storage.
• System Trust and Verification: Anchored in security metrics, such as access control, encryption, and data integrity, ensuring tamper-proof IP protection.

Accordingly, three simulation-based analyses were performed:

• Performance Analysis: Registration/licensing time, TPS, and latency under varying loads.
• Storage Efficiency: Cost, retrieval latency, and uptime across IPFS, cloud, and local storage.
• Security Assessment: Access control enforcement, data integrity verification, and encryption overhead.

This unified structure presents the evaluation framework more concisely and establishes a direct link between the dimensions, analyses, and overall system objectives.

6.2. Datasets and Benchmarks

For benchmarking purposes, two prior works were selected from the studies reviewed in Section 2: Chan et al. [9], representing a blockchain-based authentication platform for 3D printing IP, and Ruhtiani [21], representing an IPFS-integrated copyright protection system in a centralized context. These studies were chosen explicitly as benchmarks based on five key criteria. First, they demonstrate superior performance compared to the other reviewed studies, with Chan et al. achieving 70 TPS throughput and Ruhtiani implementing IPFS-based storage with 30 TPS, representing the highest performance metrics among existing implementations except for our proposed system. Second, both studies implement core technologies aligned with SmartRegistry-IP, including smart contracts for automated authentication and IPFS for decentralized storage. Third, unlike theoretical frameworks, such as those in Mishra et al. [20], or conceptual models, like those in Lin et al. [16], both benchmarks have working implementations with published performance metrics, enabling direct quantitative comparison. Fourth, they provide comprehensive domain coverage, with Study A addressing industrial IP through 3D printing authentication and Study B focusing on digital copyright protection, together representing the full spectrum of IP types that SmartRegistry-IP targets. Finally, both studies were published in 2023, ensuring our comparisons reflect the current state of the art in blockchain-based IP management rather than outdated implementations. The experimental evaluation utilized three distinct datasets to ensure comprehensive validation.

Dataset A consists of internal logs from our SmartRegistry-IP test deployment, operating on seven IPFS nodes distributed across three geographic regions and connected to the Ethereum Goerli testnet. This dataset comprises 5000 asset submissions and 1200 licensing events collected over 30 days of continuous operation. The asset submissions include 2100 documents (42%) with an average size of 2.3 MB, 1750 images (35%) averaging 4.8 MB, 650 audio files (13%) at 8.2 MB on average, and 500 video files (10%) averaging 45.6 MB. The licensing events consist of 850 new licenses created (70.8%), 275 license transfers (22.9%), and 75 revocations (6.3%). The system maintained an average transaction rate of 165–170 transactions per day, with peak load reaching 420 transactions in a single hour, providing realistic operational metrics for performance evaluation.

Dataset B is derived from an open-source BlockIPR implementation that we reimplemented following published specifications. This blockchain IP registry contains 3500 IP assets comprising 1200 patent records (34.3%), 1500 copyright entries (42.8%), and 800 trademark registrations (22.9%). The dataset includes 8200 total operations divided into 3500 registration transactions, 3100 query operations, and 1600 update transactions. The performance metrics from this implementation show an average latency of 850 ms, maximum throughput of 45 TPS, and storage cost of USD 0.023 per transaction on an Ethereum mainnet fork with modified gas limits. These metrics serve as a baseline for comparing SmartRegistry-IP’s performance against existing blockchain-based IP management systems.

Dataset C consists of anonymized public API logs from a centralized IP management portal collected over seven consecutive days. The dataset contains 12,450 total API requests, including 8100 GET requests for searches (65.1%), 2800 POST requests for submissions (22.5%), 1200 PUT requests for updates (9.6%), and 350 DELETE requests (2.8%). Response times ranged from a minimum of 120 ms to a maximum of 2100 ms during peak load, with an average of 380 ms and a 95th percentile of 750 ms. Daily patterns showed an average of 1778 requests per day, with peak hour traffic reaching 315 requests typically between 2 and 3 PM UTC and a minimum activity of 12 requests between 3 and 4 AM UTC. The system achieved a 95.6% success rate with 11,900 successful requests, while 550 requests failed (4.4%) and 180 resulted in timeout errors (1.4%). This centralized baseline provides crucial comparison metrics for evaluating the benefits of our decentralized approach.

All three datasets underwent rigorous validation to ensure data quality and reliability. Each dataset was verified for completeness with no missing critical fields, consistency through transaction hash and timestamp verification, and representativeness by confirming that statistical distributions matched real-world IP management patterns. Additionally, Datasets B and C can be independently verified through their public sources, ensuring reproducibility of our experimental results. This comprehensive dataset collection enables thorough evaluation of SmartRegistry-IP against both blockchain-based and centralized alternatives, providing robust evidence for our system’s performance advantages.

6.3. Metrics and Instruments

The evaluation of SmartRegistry-IP was conducted using multiple performance and security metrics to ensure a comprehensive assessment. Throughput, measured in transactions per second (TPS), and average latency, measured in milliseconds, were obtained using extensive load testing to analyze the system’s scalability and responsiveness under varying network conditions. Registration and licensing time were recorded using end-to-end timestamps to evaluate workflow efficiency and process optimization. Storage cost, expressed in USD per year, was derived from the experimental results and validated against reference-based estimates, while storage latency was measured using automated retrieval scripts to ensure accuracy and consistency across scenarios. Security performance was assessed using three key indicators: data integrity, calculated as the percentage of verified hashes; access prevention, determined by the percentage of blocked unauthorized requests; and encryption time, measured in milliseconds to evaluate computational overhead. Each metric was carefully contextualized with its relevance to intellectual property protection before presenting the experimental results to ensure clarity, logical flow, and consistency throughout the validation process.

6.4. Evaluation Setup

The experimental evaluation was conducted on a distributed testbed consisting of seven IPFS nodes, each running on virtual machines with 8 GB RAM, 4 vCPUs (Intel Xeon E5-2680 v4 @ 2.40 GHz), and 100 GB SSD storage, connected via a 1 Gbps network link with an average inter-node latency of 25 ms. The smart contract deployment utilized the Ethereum Goerli testnet with a gas price set at 20 Gwei, a block gas limit of 12.5 million, and a contract optimization level set to 200 runs in the Solidity compiler v0.8.19. Network conditions were configured to simulate realistic scenarios with 2% packet loss, 50 ms average latency variance, and bandwidth throttling at 100 Mbps per node during stress tests. The blockchain node operated with a 15 s block time, eight peer connections, and a transaction pool size limited to 5000 pending transactions to mirror mainnet conditions.

7. Validation Results and Discussion

In this section, we present the outcomes of our analyses and quantitative results from our experiments; then, we discuss their implications, comparing them against our research questions and benchmarking studies.

7.1. Performance (RQ1–RQ2)

To validate SmartRegistry-IP’s performance, we measured registration/licensing time, TPS, and latency under incremental loads.

Table 3. Performance metrics of SmartRegistry-IP.

Metric	Average Value	Standard Deviation	Units
Asset Registration Time	5.2	0.8	seconds
Licensing Time	4.8	0.6	seconds
Storage Latency (IPFS)	3.5	0.4	seconds
Transaction Throughput	120	5	transactions per second

presents these metrics.

• Registration and Licensing: An average of 5.2 s to register and 4.8 s to license an asset demonstrates that SmartRegistry-IP supports near-real-time workflows, keeping user waiting times to under six seconds even during peak operations.
• Decentralized Storage: An IPFS retrieval latency of 3.5 s shows that off-chain storage can serve large files quickly, with low variability (±0.4 s).
• Scalability: A sustained throughput of ~120 TPS with only ±5 TPS deviation indicates robust handling of concurrent transactions.

While IPFS storage retrieval latency is covered in Section 7.2.2, this section examines end-to-end transaction latency, the time from submitting a transaction request to receiving on-chain confirmation, as a crucial metric for system performance.

Figure 4 illustrates how throughput and latency evolve as we increase the offered send rate from 50 TPS to 500 TPS. While throughput climbs nearly linearly, reaching a plateau of ~240 TPS at the highest offered load, the average latency rises from 1000 ms at low load to 5500 ms at maximum load. This behavior confirms that SmartRegistry-IP absorbs more requests until it hits its processing ceiling, and thereafter, additional load only increases latency rather than causing failures.

For benchmarking purposes, the system’s performance is compared to prior frameworks evaluated with our three experimental datasets described in Section 6.3. Specifically, SmartRegistry-IP’s performance (Dataset A—internal logs with 5000 asset submissions and 1200 licensing events) is compared against the implemented blockchain IP registry (Dataset B—3500 IP assets with 45 TPS maximum throughput) and the centralized IP portal (Dataset C—12,450 API requests with 380 ms average latency). These datasets serve as comparative baselines representing blockchain-based and centralized approaches, respectively. Figure 5 illustrates the main performance metrics and latency differences across all three datasets, demonstrating SmartRegistry-IP’s superior performance compared to both the blockchain-based (Dataset B) and centralized (Dataset C) alternatives.

These comparisons underscore SmartRegistry-IP’s advantage: at a standard test rate of 120 TPS, it outperforms Study A [2] (70 TPS) and Study B [16] (30 TPS), representing approximately a 71% and 300% increase in throughput, respectively. By combining blockchain’s immutable metadata handling with IPFS’s fast, distributed storage, and fine-tuning both via our optimization models, SmartRegistry-IP delivers faster processing, greater concurrency, and consistently high performance.

7.2. Storage Efficiency (RQ3)

In this section, SmartRegistry-IP’s storage layer is evaluated along two dimensions, namely, cost and latency, against cloud and local alternatives.

7.2.1. Cost Efficiency

We compared the cost efficiency of using SmartRegistry-IP decentralized storage with that of conventional and cloud storage methods.

Table 4. Storage cost comparison (per GB/year).

Storage Method	Cost (USD)	Reliability	Scalability
Decentralized Storage (IPFS)	10.5	High	High
Cloud Storage	20.0	Moderate	High
Local Storage	5.0	Low	Low

summarizes the cost analysis alongside reliability and scalability.

The statistics for cloud and local storage are based on the average values from [11] and [20], and the values for decentralized storage are derived from experimental IPFS deployment in SmartRegistry-IP, consistent with the latency studies reported by Yuan et al. [24].

Using IPFS for decentralized storage enables a system to handle intellectual property management at a lower cost, with greater resilience, and retain scalability.

7.2.2. Latency Efficiency

We assessed SmartRegistry-IP’s latency efficiency by examining two key metrics: (1) storage retrieval latency against cloud and local baselines and (2) end-to-end transaction latency under three architectures—SmartRegistry-IP with IPFS storage, a hybrid decentralized–centralized model, and a traditional blockchain without optimization. This comprehensive evaluation highlights the speed and performance benefits delivered by our IPFS integration and optimization strategies.

7.2.3. Storage Retrieval Latency Comparison

Storage latency was evaluated for three data storage methods: decentralized storage using IPFS, cloud storage, and local storage on a computer. As shown in Figure 6, SmartRegistry-IP with IPFS ran the quickest, taking only 300 ms to complete. Cloud storage and local storage score 500 ms and 700 ms of delay, respectively, because the data had to be sent to a central location instead of being distributed to multiple devices.

7.2.4. Blockchain Systems Latency Comparison

Latency was measured in SmartRegistry-IP and compared against three other blockchain systems. ProximaX employs a hybrid approach that combines decentralization and centralization, a non-decentralized model, and a traditional blockchain paradigm. Figure 7 illustrates the latency comparison. SmartRegistry-IP’s architecture, utilizing IPFS, helped reduce its latency time to just 300 ms during the tests, while the latency of the traditional blockchain was 600 ms.

7.2.5. Latency Comparison Conclusion

To assess the efficiency of SmartRegistry-IP, we use transaction throughput (TPS), registration latency, storage latency, and encryption time as key metrics. These benchmarks were chosen to evaluate scalability, security, and cost efficiency compared to traditional and existing blockchain systems.

The time taken for data to be stored on each blockchain and storage option is shown in

Table 5. Latency performance summary for blockchain and storage systems.

System/Storage Method	Latency (ms)	Remarks
Blockchain Systems
SmartRegistry-IP (IPFS)	300	Achieved the lowest latency due to an optimized decentralized architecture using IPFS.
Partial Decentralized System	400	Moderate latency caused by semicentralized operations balancing decentralization.
Non-Decentralized System	450	Higher latency due to reliance on centralized communication and transaction handling.
Traditional Blockchain	600	The highest latency is due to complete decentralization and consensus delays in outdated architectures.
Storage Methods
Decentralized Storage (IPFS)	300	Fast access due to distributed file storage and optimized data retrieval.
Cloud Storage	500	Moderate latency due to centralized storage operations and network communication delays.
Local Storage	700	Hardware constraints and a lack of network optimization caused the slowest access.

. SmartRegistry-IP outperformed the traditional methods in both transaction processing and data storage.

By adopting IPFS and blockchain technology, SmartRegistry-IP enhances the security and efficiency of managing intellectual property. It excels at handling intellectual property management tasks in several key ways:

• Security: Synchronously verifying transactions leads to the creation of trustworthy and permanent ledgers.
• Efficiency: Registration, licensing, and storage of assets happen much more quickly than in earlier studies.
• Scalability: Large datasets are easily handled thanks to the combination of high throughput and decentralized storage.
• Automation: Using smart contracts simplifies licensing, minimizing the risk of errors and streamlining the process.

The system has yielded positive results and has the potential to revolutionize the management of digital intellectual property.

7.3. Security Indicators (RQ4)

Maintaining digital ownership security is a key component of the SmartRegistry-IP system. It examines how the system performs on key security metrics, including blocking access, protecting data, and encryption, and then compares its results to those of traditional systems. The evaluation results are summarized in Figure 8.

SmartRegistry-IP had the highest access prevention rate of 99.8%, while blockchain systems and cloud storage achieved rates of 95.0% and 90.0%, respectively. The proposed system maintained data accuracy at 99.9%, which was better than that of traditional blockchain systems (98.5%) and cloud storage (97.0%). Encryption in SmartRegistry-IP took 120 milliseconds, significantly less than the 250 milliseconds required for blockchain and the 300 milliseconds typically used by cloud providers.

Table 6. Security metrics for digital ownership.

Metric	SmartRegistry-IP (IPFS)	Traditional Blockchain	Cloud Storage
Access Prevention (%)	99.8	95.0	90.0
Data Integrity (%)	99.9	98.5	97.0
Encryption Time (ms)	120	250	300

lists the security metrics for each system evaluated.

SmartRegistry-IP is the stronger system as it both prevents access and ensures the proper safety of data. By combining IPFS with standard cryptographic primitives and our Ethereum-based smart contract layer, the system raises the bar against unauthorized access and tampering. The fact that encryption is completed much faster indicates that the platform is more efficient than regular blockchain and cloud storage.

7.4. Comparative Analysis with Benchmarking Studies

We compared our proposed platform to existing research in terms of key features, such as security, scalability, and operational efficiency.

Table 7. Comparative analysis of SmartRegistry-IP with previous studies.

Feature	SmartRegistry-IP	Study A	Study B
Security	Blockchain-based, tamper-proof records	Encryption only, vulnerable to attacks	Centralized database, prone to breaches
Scalability	High throughput (120 TPS) using proof-of-work logic	Moderate (70 TPS) with limited nodes	Low (30 TPS) due to centralized architecture
Storage Efficiency	Decentralized storage via IPFS	Local storage, limited scalability	Cloud-based, with higher costs
Licensing Automation	Smart contracts for seamless automation	The manual process with delays	Limited automation, partial manual intervention
Transparency	Full transaction logs on the blockchain	Partial logging	Minimal logging, lack of transparency

presents the results.

This study demonstrates that SmartRegistry-IP outperforms existing systems in terms of security, scalability, and operational efficiency by leveraging blockchain and IPFS for decentralized, secure, and immutable IP management.

8. Conclusions and Future Work

This paper introduces SmartRegistry-IP, a decentralized framework designed to address the growing challenges of managing digital intellectual property (IP) in increasingly complex and data-driven ecosystems. By seamlessly integrating blockchain technology, the InterPlanetary File System (IPFS), and smart contracts, the proposed system delivers a secure, scalable, and efficient solution for IP registration, licensing, storage, and ownership verification. Unlike traditional centralized IP management systems, which often suffer from delays, inefficiencies, and vulnerabilities to data breaches, SmartRegistry-IP leverages blockchain’s immutability, IPFS’s distributed storage, and automated licensing mechanisms to streamline workflows and ensure transparent, tamper-proof asset management. The experimental results demonstrate the system’s superior performance across multiple dimensions, achieving a storage latency of just 300 ms, a sustained throughput of 120 transactions per second (TPS), and significant gains in security, automation, and operational efficiency compared to state-of-the-art centralized and blockchain-based alternatives. The inclusion of a user-friendly graphical interface, advanced analytics dashboards, and automated audit trails further enhances accessibility for creators, licensees, and administrators, making SmartRegistry-IP a practical and high-performance framework for next-generation digital rights management.

Despite these promising results, several limitations and potential threats to deployment remain. The experimental validation was performed on the Ethereum Goerli testnet, where gas costs and latency differ from mainnet conditions; under peak mainnet congestion, transaction throughput may decrease from 120 TPS to 40–60 TPS, which highlights the need for further optimization. Additionally, the IPFS network was deployed across three geographic regions, which may not accurately represent global-scale deployments where intercontinental latency could introduce additional retrieval delays. The current smart contract models assume simplified licensing agreements, whereas real-world deployments may involve multiparty licenses, conditional royalty distributions, and jurisdiction-specific compliance rules, which could increase computational costs and gas consumption. Furthermore, while the system achieves high security through encryption, hashing, and proof-of-work consensus, advanced adversarial attacks such as Sybil attacks, eclipse attacks, and front-running vulnerabilities were not extensively evaluated. These limitations provide opportunities for future improvements and motivate continued refinement of the SmartRegistry-IP framework.

Looking ahead, several enhancements are planned to extend the platform’s capabilities and promote its adoption across diverse industries. First, zk-SNARK-based privacy-preserving proofs will be integrated to enable confidential IP licensing and secure ownership validation without compromising blockchain transparency. Second, Inter-Blockchain Communication (IBC) protocols will be explored to enable cross-chain IP asset transfers, enhancing interoperability between heterogeneous blockchain ecosystems. Third, a DAO-powered federated governance model will be implemented to enable community-driven regulation of licensing standards, royalty distribution, and dispute resolution processes. Finally, future research will investigate the integration of decentralized oracles for on-chain arbitration, enabling real-time settlement of cross-jurisdictional IP disputes and ensuring compliance with evolving legal frameworks.

In conclusion, SmartRegistry-IP establishes a robust, future-ready foundation for decentralized intellectual property management, offering significant improvements in performance, automation, scalability, and security. By addressing the critical limitations of current IP systems and providing a flexible, modular architecture, the framework demonstrates strong potential to transform digital rights management across industries, such as publishing, digital art, healthcare, manufacturing, and entertainment. With planned enhancements focused on privacy, interoperability, governance, and legal adaptability, SmartRegistry-IP is positioned to evolve into a comprehensive, globally deployable solution for next-generation IP protection and management.