5.1. Test Environment Setup
To evaluate the gas efficiency and transaction throughput of our system on Ethereum Layer 1, we conducted a series of performance benchmarks using Hardhat, a widely adopted development framework for Ethereum. All experiments were executed on a local Hardhat network running on a single machine, simulating 300 distinct accounts.
We focused exclusively on state-changing functions, including applyPassport, approveApplication, issuePassport, rejectApplication, grantAccess, revokeAccess, grantAccessBatch, and revokeAccessBatch.
To simulate varying transaction loads, we designed a benchmarking harness that sends transactions at predefined rates (e.g., 10, 20, …, up to 300 tx/s) for a fixed duration of 5 s per rate. These experiments measure both the gas consumption of individual functions and the overall system throughput.
5.2. Test Result and Evaluation
5.2.1. Gas Consumption
We first evaluated the gas consumption of each key state-changing function in the system. All functions were executed under controlled conditions on a local Hardhat network. The values reported represent the average gas used, calculated over multiple runs with different user accounts.
Table 6 summarizes the gas usage of the main contract functions. Functions such as applyPassport and grantAccess incur moderate gas costs, whereas issuePassport is the most expensive operation due to on-chain contract deployment. In contrast, rejectApplication and revokeAccess are relatively lightweight operations.
To contextualize the gas usage of our system, we compare it with prior work. In a similar blockchain-based identity and data-sharing platform [
23], functions such as bindAccount, setEncryptCSR, and setEncryptPrivateKey consume 737,645, 749,239, and 411,582 gas, respectively.
By comparison, our applyPassport and grantAccessBatch operations consume 140,688 and 192,971 gas, significantly lower than comparable operations in the related work. Our most expensive operation, issuePassport, which dynamically deploys a Personal Passport contract, consumes approximately 1.98 million gas. This is comparable to the createIdentityManagerContract operation in [
23], which requires around 1.42 million gas, and is considered reasonable given the on-chain deployment overhead.
These results demonstrate that the gas costs of our system are within a justifiable range for Ethereum Layer 1 smart contract operations, particularly considering the associated functionalities and on-chain data storage requirements.
5.2.2. Requirement Analysis
To estimate the system’s throughput requirements, we analyze passport issuance and usage in five populous regions: India, China, the EU, Japan, and the United States. These regions collectively represent a significant portion of the global population and international travel, providing a reasonable lower-bound reference for system demand.
We consider two primary use cases: (1) issuance of new passports and (2) write operations related to active passport usage, such as metadata updates or authorization events.
For the first scenario, China reportedly issues around 25 million new passports annually [
24]. Assuming similar issuance volumes in the other regions, we estimate a total of 125 million new passports issued per year across these five regions, or approximately 340,000 issuances per day. With three on-chain transactions per issuance, this corresponds to roughly 12 transactions per second (TPS).
The second scenario concerns ongoing usage of active passports, such as cross-border travel events that trigger on-chain operations like metadata updates or access control changes. According to travel statistics, U.S. citizens made over 90 million outbound trips in 2023 [
25], while around 170 million U.S. citizens hold valid passports [
18], suggesting that roughly 50% of passports are actively used each year. Conservatively assuming that 50% of all issued passports are used annually and that each active passport triggers five write operations on-chain per year, we calculate system demand.
Across the United States (170 M), Japan (20 M) [
26], China (200 M) [
16], the EU (200 M, assuming half hold passports), and India (90 M) [
19], there are approximately 680 million passport holders, of which 340 million are active annually. With five write operations per active passport, the system would need to support roughly 1.7 billion on-chain operations per year, equating to approximately 54 TPS.
This analysis indicates that a target throughput of around 70 TPS would be sufficient to support real-world passport issuance and usage at a global scale.
5.2.3. Function Throughput
We first conducted extensive throughput benchmarking across the state-changing functions of our system. The experiments were executed on a local Hardhat Ethereum Layer 1 network with 300 distinct accounts, simulating increasing transaction rates from 10 to 300 transactions per second (tx/s).
Among the Passport Manager contract functions, all tested operations—including applyPassport, approveApplication, issuePassport, and rejectApplication—exhibited similar throughput patterns (
Table 7,
Figure 13). As the send rate increased, throughput rose steadily to around 40–50 tx/s. This trend was consistent regardless of a function’s complexity or gas usage, suggesting that beyond a certain load, throughput is limited by external factors rather than contract logic alone.
In the Personal Passport contract, we evaluated both single-role and batch-role access control functions. Notably, grantAccessBatch and revokeAccessBatch assigned or revoked five roles in a single transaction (
Figure 14). Despite this, their measured throughput remained comparable to the non-batch versions, indicating that batching reduces gas per role but does not significantly improve raw transaction throughput. Future optimizations could explore batching in other parts of the system, such as passport issuance or metadata updates, where aggregated execution might yield greater performance benefits.
To address scalability limitations, Layer 2 solutions have been increasingly adopted. ZK-Rollup-based platforms such as zkSync Era and Polygon zkEVM have demonstrated the ability to handle thousands of transactions per second [
27,
28]. Recent measurements from blockchain explorers like Chainspect [
29] provide practical reference points for Layer 2 performance. For example, on Arbitrum [
30], an Ethereum Layer 2 solution using optimistic rollups, maximum recorded TPS per block reached 6006, with a 100-block average of 1105 TPS. These results confirm that Layer 2 solutions can sustain high throughput, supporting the feasibility of deploying high-volume applications such as cross-border passport systems on public blockchain infrastructure.
To evaluate scalability on Layer 2, we conducted throughput testing using a local Arbitrum full-chain test node. Compared to the Layer 1 results,
Table 8,
Figure 15 and
Figure 16 show a significant performance improvement across all contract functions. Many functions now exceed 150 TPS under higher load conditions, meeting the system requirements estimated in
Section 5.2.2. While these results demonstrate that Arbitrum Layer 2 can support real-world identity workloads, they remain below peak throughput levels observed on public Arbitrum chains, likely due to differences in infrastructure and performance optimizations. Public sequencers benefit from more powerful hardware and tuned configurations, allowing more efficient batching and transaction sequencing [
31].
To further investigate this performance gap, we benchmarked the applyPassport function on a higher-performance desktop with an Intel i7-12700K processor, compared to the original tests on a MacBook Air M2.
Table 9,
Figure 17 and
Figure 18 show a substantial throughput improvement, reaching up to approximately 300 TPS at 500 tx/s. This confirms that the earlier limitations were primarily hardware-bound and reinforces the conclusion that Layer 2 platforms can reliably meet the throughput requirements of our system in production environments.
Integrating our system with Layer 2 infrastructures allows it to overcome the throughput and cost limitations inherent in Ethereum Layer 1. Based on the estimated global demand for passport issuance and usage, a sustained throughput of approximately 70 transactions per second (TPS) is required. Experimental results show that while Layer 1 achieves 40–50 TPS, Layer 2 deployments exceed 150 TPS under standard testing, and can reach up to 300 TPS on high-performance hardware. These findings confirm that the system can reliably support global-scale operations and highlight the feasibility of deploying the proposed architecture in real-world scenarios.
In addition to throughput, response time is a critical performance metric for real-time passport issuance and verification. Response time is defined as the elapsed time between transaction submission and confirmation. Although this study does not directly measure confirmation latency, response time behavior can be inferred from the relationship between transaction send rate and sustained throughput. When the send rate approaches or exceeds system capacity, transactions accumulate in the mempool or sequencer queue, resulting in increased confirmation delays.
The experimental results indicate that Ethereum Layer 1 saturates at approximately 40–50 TPS, implying that higher transaction arrival rates would lead to queue buildup and prolonged response times. In contrast, the proposed Layer 2 deployment sustains significantly higher throughput, consistently exceeding 150 TPS and reaching up to 300 TPS under higher-performance environments. This increased processing capacity effectively mitigates transaction queuing under comparable workloads, thereby reducing end-to-end response times and improving system responsiveness. These results support the claim that the proposed architecture improves not only throughput and cost efficiency, but also response time, making it suitable for latency-sensitive cross-border passport operations.
5.3. Security Analysis
This section analyzes the security properties of the proposed decentralized passport management system, focusing on data integrity, access control, privacy protection, and governance trust assumptions.
First, data integrity and tamper resistance are ensured through the use of Ethereum smart contracts. Passport issuance records, access permissions, and authorization events are stored on-chain, benefiting from Ethereum’s immutability and consensus guarantees. Once recorded, these state transitions cannot be altered without detection, providing strong protection against unauthorized modification or forgery of passport data.
Second, fine-grained access control is enforced through Personal Passport smart contracts, implemented using OpenZeppelin’s role-based access control (RBAC) module. Each traveler is assigned a dedicated contract that implements RBAC, with roles defined as bytes32 constants (typically computed using keccak256 (“ROLE_NAME”)). Roles such as NAME_VIEWER and PHOTO_VIEWER can be granted or revoked individually or in batches via dedicated functions, and access permissions are checked through hasRole. This design ensures transparent, verifiable, and user-controllable authorization over which domains can access specific fields of a passport.
We acknowledge that storing RBAC metadata on-chain, even as hashed constants, may still expose certain information due to public-chain observability. For example, authorization relationships, contract or address mappings, interaction patterns, and transaction timing can potentially be inferred, especially under high-frequency cross-border usage. To mitigate these privacy risks, the system adopts several practical measures: minimizing sensitive information stored on-chain, applying batch operations and timing obfuscation to reduce correlatability, protecting off-chain data access with fine-grained RBAC, encryption, and cryptographic signatures, and randomizing certain transaction patterns where feasible. These measures reduce the risk of metadata-based profiling while preserving auditability, verifiability, and user control over data sharing.
Third, privacy protection is further achieved by minimizing the on-chain exposure of sensitive personal information. Smart contracts maintain verifiable references and access permissions, while sensitive passport data is securely managed off-chain. This approach reduces the risk of large-scale data leakage while preserving auditability and verifiability.
Finally, the proposed governance model mitigates single-authority trust assumptions through a Global Passport Registry deployed on Ethereum Layer 1 and managed via a DAO bootstrapped by ICAO. To operationalize governance in real-world scenarios, the system incorporates explicit mechanisms addressing key risks. Critical actions, such as country onboarding, contract upgrades, and emergency revocation, require multi-signature approval and threshold-based voting among DAO members. Upgrade control is enforced by requiring proposals for smart contract modifications to be reviewed and approved through the DAO before deployment, ensuring that no single entity can unilaterally modify system logic. Emergency revocation procedures enable rapid suspension of compromised roles or contracts, triggered either automatically upon anomaly detection or manually by a quorum of DAO members. Collusion risks are mitigated by distributing decision-making across multiple independent countries and enforcing voting thresholds for sensitive operations. Dispute resolution is handled via a designated arbitration contract or trusted arbitration process, providing a structured pathway for resolving conflicts or disagreements. By specifying event-triggered processes, responsibilities, and access restrictions, the governance framework ensures transparency, accountability, and operational feasibility for cross-border passport management while maintaining compatibility with Layer 2 scalability.
The proposed architecture thus provides a comprehensive set of security guarantees, including data integrity, confidentiality, fine-grained access control, decentralized governance, and privacy-aware metadata handling. Leveraging Ethereum smart contracts and Layer 2 infrastructures, the system avoids single points of control while ensuring that authorization and identity operations remain transparent, verifiable, and privacy-conscious. These security properties collectively support the deployment of the proposed system in real-world cross-border identity and passport management scenarios.
5.4. Comparison with Existing Blockchain Method
This section compares the proposed system with existing blockchain-based passport and identity management solutions, focusing on throughput, response time, and transaction cost. Prior studies commonly adopt permissioned blockchains such as Hyperledger to support digital passports or identity applications [
32,
33,
34]. While such systems can achieve low response times through localized execution, they rely on centralized or consortium-based governance and incur high operational costs due to infrastructure maintenance and limited interoperability. The comparison as shown in
Table 10.
Public blockchain–based solutions deployed directly on Ethereum Layer 1 provide stronger transparency and decentralization, but their scalability is constrained by limited throughput and high transaction fees [
35,
36]. As demonstrated in our evaluation, Layer 1 throughput saturates at approximately 40–50 TPS, making it difficult to sustain real-world, high-volume passport operations without congestion and increased confirmation delays.
In contrast, the proposed architecture combines Ethereum Layer 1 governance with Layer 2 execution for passport issuance and access control. Experimental results show that the system consistently sustains over 150 TPS and reaches up to 300 TPS under higher-performance environments, significantly exceeding both Layer 1–based approaches and the estimated system requirement. This higher processing capacity reduces transaction queuing under equivalent workloads, leading to improved response times and substantially lower transaction costs. Compared to existing solutions, the proposed system achieves a balanced trade-off between decentralization, scalability, and operational efficiency, making it better suited for large-scale, cross-border passport deployment.