Securing Critical Infrastructure with Blockchain Technology: An Approach to Cyber-Resilience
Abstract
:1. Introduction
2. Materials and Methods
2.1. Literature Review
2.2. Use-Case Analysis
2.3. Prototype Development
2.3.1. Blockchain Architecture
2.3.2. Operating Environment
2.4. Selection of Blockchain Technologies
2.5. Blockchain Efficiency Assessment
- Penetration testing: The attack model tests the blockchain’s resistance to different attack vectors, such as double spending or a 51% attack.
- Threat modeling: Used to anticipate and prepare defenses against future attacks.
- Smart contract analysis: This includes static and dynamic analysis of the code and formal verification.
- Performance benchmarking: Stress tests are conducted to evaluate network scalability and performance under high transactional loads, using the following equation to calculate transaction throughput (TR):
2.6. Implementation of the Blockchain Solution
2.7. Validation and Verification
2.7.1. Impact Analysis and Return on Investment
- Transaction processing time (TPT): The average transaction processing times before and after implementing the blockchain solution are compared.
- Transaction error rate (TER): The error rates in transactions and records are measured before and after implementation.
- Frequency of security incidents (FSI): Cybersecurity incidents are recorded.
2.7.2. Contingency and Recovery Plan
2.7.3. Feedback and Continuous Improvement
- Surveys and forms: Periodic online forms are designed to make it easier for users to communicate their experiences and suggestions.
- Focus groups and interviews: Focus group sessions and individual interviews are conducted to better understand the qualitative feedback.
- Ticket and support system: A ticket management system is established that allows users to report problems and suggestions.
- Response time: The mean and variance of response time are performance indicators.
- Successful transaction rate: The proportion of transactions completed without errors is calculated.
- Resource usage: Resource usage, such as CPU, memory, and storage, is analyzed to optimize system configuration and improve efficiency.
- Security and vulnerabilities: The platform’s security is monitored, including intrusion attempts, flaws, and other vulnerabilities.
3. Results
3.1. Blockchain Technologies
3.2. Performance Analysis in Supply Chain Management
3.3. Blockchain Efficiency and Implementation Challenges Assessment
3.4. Evaluation and Results of the Implemented Blockchain Solution
3.5. Evaluation of Results and Return on Investment
3.6. Feedback and Sustained Optimization
- Risk assessment and analysis: Carrying out periodic risk assessments to identify and classify possible threats to the platform’s security.
- Prevention strategies: To reduce the attack surface, preventive security measures such as data encryption, multi-factor authentication, and advanced firewalls are applied.
- Incident detection and response: Establishment of an intrusion detection system and an incident response protocol to act quickly against any security threat.
- Recovery and resilience: Develop disaster recovery and business continuity plans to ensure rapid service restoration in the event of serious incidents.
- Training and awareness: Implement security training programs for employees and end users, increasing awareness of security practices and reducing the risks of human error and social engineering attacks.
- Ease of use: This metric, measured on a scale from 0 to 10, reflects users’ subjective experience when interacting with the platform. An increase in this score indicates an improvement in the platform’s intuitiveness and accessibility, facilitating its adoption and daily use.
- Overall satisfaction: Also measured on a scale of 0 to 10, this metric captures the user’s overall perception of the solution, considering efficiency, reliability, and convenience. A higher overall satisfaction score suggests that the solution’s implementation has positively impacted the user experience.
- Support response time: Evaluate how quickly the support team responds to queries or problems users report. This time is measured in hours, and a reduction indicates an improvement in support efficiency, contributing to a better user experience.
- Transaction error rate: This metric, expressed as a percentage, measures the frequency of errors during transactions. A decrease in the error rate signals better reliability and stability for the platform after implementing the blockchain solution.
- Downtime (hours per month): This measures the time the platform is not operational or accessible to users in a month. Reducing downtime indicates a significant improvement in platform availability and robustness.
3.7. Identity Management System in Blockchain Implementation
3.8. Comparative Analysis of Alternative Solutions
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Blockchain Technology | Scalability (TPS) | Security (Past Audits) | Integration (Development Hours) | Regulatory Compliance (Conformity Score) | Energy Consumption (kWh per Transaction) | Adoption Rate (%) |
---|---|---|---|---|---|---|
Ethereum | 30 | 95 | 200 | 85 | 0.05 | 65 |
Hyperledger Fabric | 3000 | 98 | 150 | 90 | 0.01 | 40 |
Chain | 1 | 97 | 180 | 88 | 0.015 | 25 |
Quorum | 2 | 96 | 160 | 87 | 0. | 30 |
Rhode Island | 1 | 92 | 220 | 80 | 0.03 | 20 |
EOS | 4 | 90 | 300 | 75 | 0.02 | 15 |
Performance Metrics | Before Implementation | After Implementation | Improvement (%) |
---|---|---|---|
Transaction processing time (seconds) | 10 | 5 | 50 |
Transaction error rate (%) | 5 | 1 | 80 |
Incident response time (hours) | 48 | 24 | 50 |
Cost per transaction (USD) | 1.50 | 0.75 | 50 |
Traceability of products in the chain (%) | 75 | 95 | 26.67 |
Evaluation Criteria | Tela Hyperledger | Ethereum | Quorum | Corda | Ripple | EOS |
---|---|---|---|---|---|---|
Successful transaction rate (%) | 99.8 | 98.5 | 99.2 | 99.5 | 99 | 98.7 |
Average confirmation time (s) | 1.2 | 15 | 5 | 3 | 4 | 2 |
Recorded security incidents | 2 | 10 | 5 | 3 | 6 | 8 |
Tamper resistance (score) | 9.8 | 8.5 | 9 | 9.3 | 8.7 | 8.9 |
Energy consumption efficiency (kWh per 1000 Tx) | 0.5 | 50 | 20 | 10 | 15 | 25 |
Scalability (TPS) | 3.000 | 30 | 2.500 | 1.000 | 1.500 | 4.000 |
Response time in network partition simulation (s) | 0.8 | 60 | 10 | 5 | 12 | 4 |
Smart contract effectiveness (Score) | 9.5 | 9 | 9.2 | 9.4 | 8.8 | 9.1 |
Challenge | Metrics | Analysis Result | Observations |
---|---|---|---|
Scalability | TPS | 1500 TPS in optimal conditions; drops to 300 TPS under heavy load | Demand spikes significantly impact network performance. |
Interoperability | Number of systems successfully integrated | 5 of 10 fully integrated legacy systems | Differences hamper full integration in protocols and standards. |
Regulation | Number of compliance requirements satisfied | 20 of 25 requirements met | Some regulatory requirements are only possible to implement with affecting functionality. |
Evaluated Aspect | Result Description | Mitigation Measures Adopted |
---|---|---|
Integration with existing systems | 80% successful integration, with challenges in legacy systems. | Development of adapters and custom APIs. |
Implementation time | Implementation completed in 6 months, 1 month ahead of estimate. | Process optimization through agile methodologies. |
Security incidents | Three minor incidents related to network configurations. | Reinforcement of security protocols and cybersecurity training. |
User training | 75% of users achieved operational competence in 3 months. | Implementation of a continuous training program and online support. |
User adoption | Initial adoption of 60% with resistance to change. | Awareness campaigns and demonstration of tangible benefits. |
Post-implementation performance | There is a 25% improvement in operational efficiency and a 20% reduction in transaction processing time. | Continuous monitoring and configuration adjustments based on feedback received. |
Parameter | Pre-Implementation | Post-Implementation | Change (%) |
---|---|---|---|
Operating costs (annual) | USD 250,000 | USD 200,000 | −20% |
Transaction processing Efficiency (%) | 80% | 95% | 18.75% |
Security incidents | 10 | 2 | −80% |
Processing time (average, seconds) | 5 s | 2 s | −60% |
Return on investment (ROI, %) | N/A | 25% | Change (%) |
Evaluated Aspect | Pre-Implementation Score | Post-Implementation Score | Change (%) | User Observations |
---|---|---|---|---|
Easy to use | 6.5/10 | 8.2/10 | 26% | “More intuitive after the update.” |
Overall satisfaction | 7.0/10 | 8.5/10 | 21% | “Significant improvements in efficiency.” |
Support response time | 48 h | 24 h | −50% | “Faster and more efficient support.” |
Transaction error rate | 5% | 2% | −60% | “Fewer errors and greater reliability.” |
Downtime (hours per month) | 10 h | 2 h | −80% | “Greater availability of the platform.” |
Period/Circumstance | TPT | FSI | User Satisfaction (%) | Observations |
---|---|---|---|---|
Start of implementation | 1.2 s | 30 incidents/month | 70% | Initial base |
After 1st improvement | 1.0 s | 25 incidents/month | 75% | Improvement in TPT |
After 2nd improvement | 0.9 s | 20 incidents/month | 80% | FIS reduction |
Training implementation | 0.85 s | 18 incidents/month | 85% | Training impact |
Security update | 0.80 s | 15 incidents/month | 88% | Significant improvement in security |
Optimization of processes | 0.75 s | 12 incidents/month | 90% | Increased operational efficiency |
Final evaluation | 0.70 s | 10 incidents/month | 95% | Status post-improvements |
Start of implementation | 1.2 s | 30 incidents/month | 70% | Initial base |
Criterion | Proposed Blockchain Solution | Traditional Solution | Public Blockchain | Private Blockchain |
---|---|---|---|---|
Security | High | Half | High | High |
Operating efficiency | Very high | High | Half | High |
Scalability | High | Half | Low | Half |
Total cost of ownership | Half | Low | High | Half |
Return on investment | 30% | 20% | 25% | 28% |
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Govea, J.; Gaibor-Naranjo, W.; Villegas-Ch, W. Securing Critical Infrastructure with Blockchain Technology: An Approach to Cyber-Resilience. Computers 2024, 13, 122. https://doi.org/10.3390/computers13050122
Govea J, Gaibor-Naranjo W, Villegas-Ch W. Securing Critical Infrastructure with Blockchain Technology: An Approach to Cyber-Resilience. Computers. 2024; 13(5):122. https://doi.org/10.3390/computers13050122
Chicago/Turabian StyleGovea, Jaime, Walter Gaibor-Naranjo, and William Villegas-Ch. 2024. "Securing Critical Infrastructure with Blockchain Technology: An Approach to Cyber-Resilience" Computers 13, no. 5: 122. https://doi.org/10.3390/computers13050122
APA StyleGovea, J., Gaibor-Naranjo, W., & Villegas-Ch, W. (2024). Securing Critical Infrastructure with Blockchain Technology: An Approach to Cyber-Resilience. Computers, 13(5), 122. https://doi.org/10.3390/computers13050122