Blockchain Patterns in Critical Infrastructures: Limitations and

Recommendations

Hind Bangui

and Barbora Buhnova

Faculty of Informatics, Masaryk University, Brno, Czech Republic

ﬁ

Keywords:

Critical Infrastructures, Blockchain Patterns, Security, Antifragility, Resilience.

Abstract:

The widespread adoption of data-driven applications in critical infrastructures has arisen with security and pri-

vacy concerns. Blockchain has received considerable attention to protect critical infrastructures (e.g., health-

care and transportation) that could be subjected to intentional and unintentional cyberattacks. Blockchain

patterns as reusable solutions have been used in critical infrastructure software to fulﬁll security requirements

while delivering reliable and trusted services to citizens. Thus, this work provides a comprehensive review

of blockchain patterns to examine how they can steer the advancement of critical infrastructures. Through a

critical analysis of existing blockchain pattern literature, we identify realistic limitations, lessons learned and

open research issues entirely dedicated to advancing blockchain-based antifragile critical infrastructures.

1 INTRODUCTION

The digitization of critical infrastructures (CIs) has

gained increasing attention from academic and indus-

trial communities to improve the quality of citizens’

life through digital services. However, a digital CI is

not a simple technological concept that would only

merge between digital elements and physical space

to get the information and then convert it into ac-

tions for gaining smart capabilities. Instead, it also

covers the economic, social, and environmental as-

pects (Jang and Gim, 2021) that accept the digiti-

zation only if it fulﬁlls the protection requirements,

such as the absence of unacceptable failures in vital

services (like healthcare). In this regard, the differ-

ent CI deﬁnitions have mainly pointed out the impor-

tance of protecting CIs. For example, the EU Direc-

tive 2008/114/EC (Directive, 2008) has deﬁned CIs

as followed: ”A critical infrastructure means an as-

set, system or part thereof located in Member States

that is essential for the maintenance of vital societal

functions, health, safety, security, economic or social

well-being of people, and the disruption or destruc-

tion of which would have a signiﬁcant impact in a

Member State as a result of the failure to maintain

those functions”.

In the digital era, the fundamental problem of

https://orcid.org/0000-0003-2689-0382

https://orcid.org/0000-0003-4205-101X

CIs centers around the protection of their informa-

tion to guarantee the continuity and quality of their

vital services (Silva et al., 2018). Thus, the applica-

tion of blockchain technology has been extended re-

cently to CIs (Vance and Vance, 2019) as a trusted

security solution to protect sensitive CI information.

Thanks to the blockchain characteristics, e.g., trans-

parency, trust, integrity, and redundancy (Vance and

Vance, 2019), blockchain (Vance and Vance, 2019)

has received positive sightings in CIs due to its capa-

bility to enhance their properties, such as resilience

and reliability (Gheorghe et al., 2018). However,

due to the signiﬁcant blockchain impact on control-

ling the CI information and the apparition of security

concerns entirely dedicated to blockchain technology

(Boireau, 2018), a critical question has been raised in

academic and industrial communities on whether the

blockchain is capable of supporting the development

of CIs (Venkatesh et al., 2020).

Therefore, in this paper, we contribute to the body

of knowledge on blockchain and its effective adoption

for CI development by examining blockchain patterns

as reusable solutions in improving the design qualities

of CIs (like transportation). To this end, we focus on

studying only the blockchain patterns that have been

deployed in real-world scenarios in order to examine

convincingly the positive and negative realistic effects

of blockchain. Accordingly, we outline a research

agenda for blockchain patterns to meet the require-

ments of CIs that are paving the way for constructing

Bangui, H. and Buhnova, B.

Blockchain Patterns in Cr itical Infrastructures: Limitations and Recommendations.

DOI: 10.5220/0011278500003266

In Proceedings of the 17th International Conference on Software Technologies (ICSOFT 2022), pages 457-468

ISBN: 978-989-758-588-3; ISSN: 2184-2833

457

Table 1: Blockchain Application Examples in Healthcare and Transportation.

Paper Description

Healthcare Domain

(Nguyen et al., 2021) A Cooperative Architecture of Data Ofﬂoading and Sharing for Blockchain-based Healthcare Systems

(Chelladurai and Pandian, 2021) A novel blockchain based electronic health record automation system for healthcare

(Alzubi, 2021) Blockchain-based Lamport Merkle Digital Signature: Authentication tool in IoT healthcare

(Soni and Singh, 2021) Blockchain-based security & privacy for biomedical and healthcare information exchange systems

(Rajput et al., 2021) A Blockchain-Based Secret-Data Sharing Framework for Personal Health Records in Emergency Condition

Transportation Domain

(Zhang et al., 2020) BSFP: Blockchain-Enabled Smart Parking with Fairness, Reliability and Privacy Protection

(Ge et al., 2020) A semi-autonomous distributed blockchain-based framework for UAVs

(Bera et al., 2021) Private blockchain-based access control mechanism for unauthorized UAV detection and mitigation in In-

ternet of Drones environment

(Gupta et al., 2021) Blockchain-assisted secure UAV communication in 6G environment

(Alsamhi et al., 2021) Blockchain for Decentralized Multi-Drone to Combat COVID-19

(

Alvares et al., 2021) Blockchain-Based Solutions for UAV-Assisted Connected Vehicle Networks in Smart Cities

a sustainable digital world.

The remainder of the paper is structured as fol-

lows. Section 2 brieﬂy illustrates some blockchain

application examples in CIs. Section 3 carries out

a literature review on blockchain patterns that have

been applied in real-world blockchain-based appli-

cations. Moreover, it discusses the pros and cons

of blockchain patterns from the critical infrastructure

perspective. Sections 4 illustrates an advanced in-

tegration of blockchain in CIs. As blockchain pat-

terns would be merged with CIs, Sections 5 high-

lights some recommendations that could help in deal-

ing with the negative impacts associated with reusing

blockchain patterns. Finally, Section 6 concludes the

work and outlines the future research.

2 BLOCKCHAIN APPLICATION

IN CIs

Blockchain has been adopted in different CI domains

thanks to its ability to ensure preventative security

measures necessary to sustain the development of

their applications. Table 1 illustrates some of the vi-

tal domains where the blockchain has received con-

siderable interest. Indeed, blockchain has been used

in effective ways to improve the reliability of numer-

ous applications, such as the unmanned aerial vehi-

cles (UAV) that have become a big research topic

thanks to their various applications in various do-

mains, such as UAVs (or drones) for medical appli-

cations (Egala et al., 2021), multi-drone to combat

COVID-19 (Alsamhi et al., 2021), and UAV-assisted

connected vehicle networks (

Alvares et al., 2021). In-

deed, blockchain offers trust and security to UAVs

that are necessary to resist potential cyber-attacks

(e.g., Sybil and GPS spooﬁng attacks), which may

lead to the destruction of available information among

the whole UAV system. Blockchain also enhances the

coordination between distributed UAVs by solving the

computation and storage overhead issues while main-

taining its reliability and security beneﬁts.

Despite the positive inﬂuence of blockchain in

different domains, blockchain is vulnerable to sev-

eral threats (Wang et al., 2019; Boireau, 2018), such

as mining-pool threats that exploit miners to launch

attacks (e.g., Pool Hopping (Singh et al., 2019)).

Thus, the next section we focus more on examining

blockchain patterns as reusable solutions in CIs while

pointing out their limitations to determine what kind

of blockchain issues that may impact CI protection.

3 BLOCKCHAIN PATTERNS

Due to the importance to provide a proven blockchain

design for CIs, blockchain patterns are used to aid in

offering best practices for blockchain solutions and

addressing common software engineering problems.

Furthermore, patterns facilitate the design of a dis-

tributed ledger system that is a crucial part of the de-

pendability of CIs. In this respect, the aim of this sec-

tion is to study how the properties and limitations of

blockchain patterns could affect CIs.

3.1 Selection of Blockchain Patterns

From the perspective of software and systems en-

gineering, we conducted a survey of blockchain-

patterns literature, spanning from 2008 to the time

of writing this paper. Different combination of key-

words were used to ﬁnd relevant studies, such as

“Blockchain” and ”design pattern”, ”Blockchain” and

”architectural patterns”, “Blockchain patterns”, and

”blockchain-based patterns”. Furthermore, for each

paper, the title and abstract were examined dur-

ing the initial search to ensure that the paper per-

tained to blockchain patterns. Overall, 77 articles

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Table 2: Selected Blockchain Pattern Studies.

Ref Category of Patterns Sub-Category of Patterns

What kind of real-world case

study is discussed?

The major issues detected and

discussed

(Xu et al.,

2018) Smart Contract Patterns

N/A

General Examples of Real-

World Known Uses of Patterns

Limited upgradability, extra cost,

lack of ﬂexibility and adaptability

(Zhang et al.,

2017)

A Case Study on a Real-

World Blockchain-based Health-

care Applications

Extra Cost, latency,leaked Data

(Wohrer and

Zdun, 2018;

Marchesi

et al., 2020;

ohrer

and Zdun,

2018; Bar-

toletti and

Pompianu,

2017)

Ethereum Smart Contract Pat-

terns

N/A

A Case Study on a Real-World

Ethereum Blockchain-based Ap-

plication

Harmful callbacks, adverse circum-

stances on how and when func-

tions are executed, uncontrollably

high ﬁnancial risks at stake, Un-

trusted external interactions, data

sharing,cascading failures (Other

platforms face similar issues as

Ethereum)

(Liu et al., 2018)Smart Contract Patterns

Creational Patterns

A Case Study on a Real-

World Blockchain-based

Traceability Applications

Extra cost, latency, complexity,

steal of digital secret key

Structural Patterns

Inter-behavioral Patterns

Intra-behavioral Patterns

(Xu et al.,

2018)

Security Patterns N/A

General Examples of Real-

World Known Uses of Patterns

Dishonest users, compromised Key,

latency, extra cost, lack of ﬂexibil-

ity and adaptability

(Xu et al.,

2018;

Weigold

et al., 2020;

Xu et al.,

2021)

Interacting with the External

World Patterns

N/A

General Examples of Real-

World Known Uses of Patterns

Trust, delay, extra cost, uncertainty,

performance, transparency, lack of

ﬂexibility and adaptability

(Ladleif

et al., 2020)

A Case Study on a Real-World

Blockchain-based Weather

Warning Applications

Performance

(Xu et al.,

2018)

Data Management Patterns

N/A

General Examples of Real-

World Known Uses of Patterns

Compromised Key, compromising

data integrity, trustworthiness, extra

cost, immutable data may be sub-

ject to brute force decryption at-

tacks

(Weber et al.,

2019)

A speciﬁc Study for Multi-

Tenant Blockchain-Based Sys-

tems

Compromising data integrity

(Eberhardt

and Tai,

2017; Chao

et al., )

Speciﬁc Studies Focusing on

Computation and Data Off-

Chaining and Maintaining the

Key properties of misused

Blockchains

Extra Cost, compromising data in-

tegrity, unavailable Data due to ma-

licious intent, leaked Data, trustless

computation

(Liu et al., 2020)Self-Sovereign Identity Patterns

Key Management Patterns

General Examples of Real-

World Known Uses of Pat-

terns

Lost or compromised master-key,

data loss, extra cost, data integrity,

trustworthiness, privacy, Latency,

Lack of ﬂexibility and adaptability

DID management Patterns

Credential design Patterns

(Bandara

et al., 2020)

Data Migration Patterns N/A

(Xu et al.,

2018)

Deployment Patterns N/A

(Lu et al., 2021)Payment Patterns

Token Design Patterns

A Case Study on a Real-

World Blockchain-based

Payment Applications

Extra cost, privacy, upgradability,

data integrity, lack of liquidity, lack

of traceability, lack of ﬂexibility

and adaptability

Seller Management Patterns

Payment Management Pat-

terns

were retrieved from academic databases and well-

known publishers such as IEEE Xplore Digital Li-

brary, ScienceDirect, ACM Digital Library, Springer,

and Google Scholar. After that, we examined each

work based on full-text read. Then, we identiﬁed the

primary studies that fulﬁlled the following criteria:

• Providing detailed blockchain pattern descrip-

tions for developers.

• Describing how to make good use of blockchain

patterns in real-world applications.

Blockchain Patterns in Critical Infrastructures: Limitations and Recommendations

459

• Listing blockchain pattern beneﬁts.

• Listing real-world blockchain pattern drawbacks.

Due to the immaturity of software engineering for

blockchain (Hakak et al., 2020), we found only 16

comprehensive blockchain pattern studies that pro-

vide details of 102 blockchain patterns and meet our

engineering perspective views. Table 2 provides more

details about the identiﬁed blockchain pattern studies.

3.2 Comparison of Blockchain Patterns

from CI Perspective

In this section, we aim to review the adaptation

and suitability of blockchain patterns for CIs. To

avoid overlapping conﬂict, the 102 blockchain pat-

terns are classiﬁed into 9 categories based on real-

world blockchain applications (Table 2), which are as

follows: Smart contract patterns, ethereum smart con-

tract patterns, security patterns, interacting with the

external world patterns, data management patterns,

self-sovereign identity patterns, data migration pat-

terns, deployment patterns, payment patterns. After

that, we focused on examining the drawbacks cited in

each work. The importance of this step is to highlight

the major blockchain pattern limitations without fo-

cusing only on promoting the beneﬁts of blockchain

properties, such as decentralization, transparency, and

immutability. Figures 1, 2, and 3 summarize the ﬁnd-

ings of the major limitations of blockchain patterns to

explore whether blockchain patterns would live up to

their CI expectations or not.

Findings on the Pattern Beneﬁts. There is no

doubt that blockchain has the potential to promote the

development of CI systems due to its ability to change

the way to store and secure sensitive information ef-

fectively against adversaries trying to access data to

control or disrupt systems, resulting in boosting the

capabilities of CI properties (Gheorghe et al., 2018).

For example, thanks to the redundancy and trace-

ability offered by blockchain, resilience and forensic

readiness can retrain data from every step of the data

generation process in CI systems. Moreover, these

CI properties have built trust in blockchain as a dis-

tributed database technology that can endorse the data

quality and guarantee the correctness of data analysis

necessary for making resilient CI systems.

Findings on the Patterns Limitations. Based on

reviewing blockchain patterns, we found that the ma-

turity of blockchain is still facing many limitations not

yet solved. The major blockchain pattern challenge is

maintaining security (Figure 1). Notably, we found

that the key compromise is the root cause of security

issues in blockchain and its dependent systems as los-

ing this unique and secret key assigned to each user

may make sensitive information accessible to unau-

thorized parties. Moreover, since the blockchain net-

work is decentralized to prevent a single point of secu-

rity failure, it is hard to identify the behavior of a ma-

licious user who gets the private key of an authorized

user. In this critical case, blockchain technology can-

not fulﬁll the requirements of CI properties, such as

self-healing resilience that needs accurate data to aid

a system to respond rapidly and recover effectively

from unexpected setbacks. Likewise, the vulnerable

codes in smart contract patterns may cause malicious

behaviors of blocks and leave CI systems seriously

vulnerable in real circumstances. For example, the

invocation of callback functions in Ethereum smart

contract patterns (Wohrer and Zdun, 2018; March-

esi et al., 2020; W

ohrer and Zdun, 2018; Bartoletti

and Pompianu, 2017) may result in giving a chance

to attackers to exploit security bugs and deteriorate

CI systems. Equally, privacy and trust are not guar-

anteed in some blockchain patterns (Figure 1) due

to the lack of security countermeasures against such

steal of the digital key and leak data. Yet, there is a

big need to maintain the security in blockchain pat-

terns, particularly, we need to ﬁx the vulnerabilities

of smart contract and ﬁnd a secured way to share

a key over blockchain networks, while guaranteeing

and centering CI systems around the promising prop-

erties of blockchain technology, such as decentrali-

sation, authentication, conﬁdentiality, integrity, and

transparency.

On the other hand, ﬂexibility, adaptability, and

upgradability of blockchain patterns (Figure 2) are ac-

companied with signiﬁcant limitations that affect the

fusion of blockchain within CI systems. For example,

in the case of the public blockchain, all smart con-

tracts by default have no owner. As a result, all partic-

ipants can access all the information and code stored

on blockchain without any special privilege. For ex-

ample, the embedded permission pattern (Xu et al.,

2018) is used to restrict access to the invocation of

the functions deﬁned in smart contracts. However, the

speciﬁed permissions cannot be updated or removed

once they are issued, which can be considered as a

lack of ﬂexibility and adaptability in CI systems. Yet,

a mechanism should be proposed to support the ﬂex-

ibility and adaptability of the embedded permission

pattern.

Long time to synchronize a large volume of trans-

actions is another gap in blockchain patterns (Fig-

ure 2) that may affect data transmission between

CI systems, resulting in compromising security con-

cerns as well as reducing the scalability and per-

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460

Figure 1: Roadmap of Blockchain Patterns with Compromised Key, Trust, and Privacy Issues.

Figure 2: Roadmap of Blockchain Patterns with Latency, Flexibility-Adaptability, and Upgradability Issues.

formance of CI systems. Double-spending (Iqbal

and Matulevi

cius, 2021) is an example of attacks in

blockchain that reﬂects the negative impact of delay

between the initiation and conﬁrmation of two trans-

actions. Indeed, double-spending is possible with

any attacker who wants to beneﬁt from time-lapse

to get the ﬁrst transaction results before other blocks

announce the invalidation of the second transaction.

Consequently, blockchain would not be the best se-

curity solution that could manage and synchronize

real-time sensitive information ﬂow over CIs. Thus,

realistic case studies are required to understand how

blockchain may process, maintain, and manage trans-

actions over different CIs. Also, experimental studies

Blockchain Patterns in Critical Infrastructures: Limitations and Recommendations

461

Figure 3: Roadmap of Blockchain Patterns with Extra Cost Issue.

are required to identify in what cases blockchain may

cause signiﬁcant delays, resulting in deﬁning the best

practices of blockchain development and supporting

data transmission that is the main key for advancing

resilient CIs.

Meanwhile, we found that sustainability is still a

key barrier to adopt blockchain in CI systems. Indeed,

the rising cost of maintaining ledgers and managing

data is of extreme concern (Figure 3). For exam-

ple, the ”Off-Chain Data Storage” pattern requires ex-

tra communication mechanisms and storage platforms

to ensure data sharing (Xu et al., 2018), which can

cause signiﬁcant extra cost for interdependent CIs.

Likewise, some blockchain patterns still need quali-

ﬁed and experienced personnel to ensure the correct-

ness of their implementation within a system, such as

Learning Curve is mandatory steep for users of DApp

Pattern (Xu et al., 2018) to understand the functional-

ity of smart contracts and know-how to verify trans-

actions.

On the other hand, it is expected that data prop-

agated over blockchain would be increased to meet

the needs of CI systems. As a result, the comput-

ing resources of blocks would be increased, result-

ing in increased CI energy use. Actually, the cur-

rent blockchain patterns focus mainly on preventing

unauthorized access that is essential for securing any

vulnerable system; however, they are not prepared to

deal with intensive data storage related to the expo-

nentially increasing complexity of dependent CI sys-

tem interactions. For example, in (Zhang et al., 2017),

a study have been conducted to determine the beneﬁts

of the application of patterns to address interoperabil-

ity in blockchain-based health applications. However,

this work has pointed out the major limitations of re-

alizing patterns on the blockchain, which are: high

computation delay, extra computation cost, and stor-

age overhead. Thus, there is a necessity to shape an

efﬁcient and sustainable blockchain that would con-

trol and manage the data generated by smart devices

while minimizing the undesirable computation and

energy cost impact in CIs.

3.3 Observations

In this section, we summarize lessons learned from

the previous section, structured into beneﬁcial prop-

erties that can be useful in reconstructing upcom-

ing blockchain patterns and supporting the fusion of

blockchain technology within complex CIs. From CI

perspective, the beneﬁcial properties of blockchain

patterns include:

• The pattern shows its simplicity for non-qualiﬁed

and experienced personnel to support its wide im-

plementation.

• The pattern shows its trustworthiness through

measuring its reputation when CI system partic-

ipants access to information.

• The pattern shows its dependability through fault-

tolerance and resilience in CI systems.

• The pattern shows its ﬂexibility and efﬁciency

through managing large datasets without develop-

ment overheads.

• The pattern shows its agility through responding

to the increasing complexity of CI system interac-

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462

tions and dealing rapidly with their related unex-

pected circumstances.

• The pattern shows its interpretability and interop-

erability through comparing and measuring alter-

native responses to automate the transformation of

interdependent and dependent CI systems.

• The pattern shows its adaptability through learn-

ing over experience and accommodating new re-

quirements imposed by the ever changing nature

of CIs (like need of using further storage space)

with minimum cost, energy, and time.

4 ADVANCED BLOCKCHAIN

APPLICATION IN CIs

Despite the blockchain pattern limitations, they can

be reused to improve the design of CIs. Thus, in

this section, we highlight an example of advanced ap-

plication of blockchain that can support the moving

beyond resilience by considering antifragility in CIs

(Sartorio et al., 2021; Martinetti et al., 2019). Besides,

we try to clarify why we should care about the limita-

tions of blockchain patterns and implications related

to them.

4.1 Data Management for Antifragile

CIs

Moving towards digitization is not an easy task for

CIs since it brings new security concerns (Sartorio

et al., 2021; Martinetti et al., 2019). Thus, CIs are

looking for strategies that enable them to learn how to

autonomously readjust and evolve their function and

structure while boosting their robustness.

Nassim Nicholas Taleb in his book ”Antifragile:

Things That Gain from Disorder” (Taleb, 2012) has

introduced the concept of antifragility as an evolu-

tionary understanding of the resilience that not sim-

ply enables a system to tolerate adverse events, but

rather allows to strengthen in the process its self-

learning ability to respond to future possible threat-

ening situations, which was clariﬁed in Taleb’s book

(Taleb, 2012) as follows: ”Antifragility is beyond re-

silience or robustness. The resilient resists shocks and

stays the same; the antifragile gets better”. Thus, an-

tifragility is a property of ”systems able to learn while

enacting elastic and resilient strategies” (De Florio,

2014). In other words, as it is impossible to predict

all future circumstances with a large negative impact

in the digital era, antifragility looks at enabling an au-

tonomous system to self-learn from shocks, resulting

in creating a complex adaptive-autonomous system

that is antifragile to negative incidents. Thus, An-

tifragility has been considered as an important step

in safety evolution (Martinetti et al., 2019), exempli-

fying the digital era. Figure 4 provides more clariﬁ-

cation concerning the antifragility concept.

4.2 Impact of Blockchain Pattern

Limitations in Antifragile CIs

Learning from disorder is the main key in antifragile

systems to boost self-improvement and autonomous

data-driven decisions (Sartorio et al., 2021; Mar-

tinetti et al., 2019). Thus, learning process should be

done through truthful information sources to satisfy

the requirements of antifragility concept. Therefrom,

blockchain is considered as the best security solution

that can manage data necessary for realizing truly an-

tifragile systems while addressing their data require-

ments in terms of trust, transparency, security, immu-

nity, redundancy, and decentralisation.

There is no doubt that blockchain can bring sig-

niﬁcant security enhancement to antifragile CI sys-

tems. However, the fusion of blockchain and antifrag-

ile CI systems is a big challenge as blockchain pat-

terns need to address carefully their limitations. For

example, due compromised key and immutable data

issues, Encrypting on-Chain Data Pattern (Xu et al.,

2018) may produce undesirable impact for antifragile

systems that center around their informational part.

5 RECOMMENDATIONS

Blockchain patterns have been merged with CIs to

support their digital transformation. However, the

blockchain pattern limitations may hinder this fusion

as any failure or attack leads to serious interdependent

cascading effects.

Therefore, in this section, we list below some po-

tential recommendations that could help in avoiding

or minimizing the negative impact of blockchain pat-

tern limitations that may affect CIs.

5.1 Distributed Trust Models for

Protecting Private CI Information

5.1.1 Description of the Challenge

Considering the limitations of blockchain patterns

detected through realistic scenarios, the users’ trust

would be affected before and after interactions with

blockchain. For example, data leakage is one of

the major privacy concerns of blockchain that pushes

Blockchain Patterns in Critical Infrastructures: Limitations and Recommendations

463

Figure 4: Antifragility Concept.

the owners of sensitive data stored in blocks to

switch from overtrust to undertrust blockchain (Zhu

et al., 2018). Indeed, in case of information leaking,

blockchain can guarantee its trustworthiness property

as stored data in blocks are unaffected and still im-

mutable, transparent, and decentralized. However, the

ledger cannot guarantee data owners’ trust as their

personal data can be disclosed without their aware-

ness and misused by unauthorized parties. The data

leakage issue could be exacerbated in CIs due to the

dependability of a set of functional services on infor-

mation. In other words, serious security issues can re-

sult in the disclosing of information and effect across

interdependent CI systems. Yet, ensuring users’ trust

through blockchain is still a big deal in CI facilities,

which are driven by the growing demand for access to

information over smart devices.

Some studies have tried to propose methodologies

for deciding the suitability of blockchain in industrial

areas (Pedersen et al., 2019; Bavassano et al., 2020).

However, they have not provided a comprehensive

guidelines on how to assess user trust who would be

willing to place data on blockchain. Moreover, they

have not discussed how to use the existing scales that

have been developed to measure user trust in various

systems, such as human-computer trust scale(Gulati

et al., 2019) and the measurement of the propensity to

trust in automation (Jessup et al., 2019).

5.1.2 Recommendation

There is a big need for proposing distributed trust

models to empower the blockchain reputation in CIs

by representing the trust level of qualitative and quan-

titative system properties, mainly privacy and safety.

5.2 Other Alternative Distributed

Ledger Technologies for CIs

5.2.1 Description of the Challenge

Despite the blockchain advantages in addressing the

correctness and trustworthiness of shared information

while preserving CI security objectives (Alcaraz and

Zeadally, 2015), the blockchain pattern drawbacks

may prevent this ledger from compelling its adoption

in CIs. To tackle these limitations, some studies

have focused on examining the suitability of each

blockchain implementation based on the character-

istics of a given application (Pedersen et al., 2019).

However, blockchain is not the only DLT (Distributed

Ledger Technology) that can ensure security and

advanced protection against threats in CIs. There

are also other DLTs that can be used as alternative

solutions for protecting CIs, such as Tangle that

is one of the most popular directed acylic graph

instances for ensuring high transaction volumes in

smart environments (Singh et al., 2021).

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464

Table 3: Comparison of Different Distributed Ledger Technologies (DLTs).

Blockchain Tangle HashGraph HoloChain Tempo

Licence Open Source Open Source Patented Open Source Open Source

Platform(s) Bitcoin, Litecoin, Ripple,

Ethereum, etc.

IOTA Swirlds Holo Radix

Initial Release 2008 2017 2016 2018 2017

Popularity Very well know Low Low Low Low

Maturity Been used Experimental Experimental Experimental Experimental

Scalability Low High High High High

Decentralized Yes Semi-Centralized Semi-Centralized Yes Yes

Energy consumption High Low Low Low Low

Mining required Yes No No No No

Transaction fees High Low Low Low Low

Transaction per second 4 to 7 500 to 800 More than 200.000 More than millions More than 25.000

Latency High Low Subject to Gossiping Subject to Gossiping Subject to Gossiping

Security in terms of Availabil-

ity, Integrity, and Fault Toler-

ance

High High High High High

Table 3 provides a comparison between the most

popular DLTs in terms of popularity, maturity, scala-

bility, decentralization, energy consumption, latency,

transaction fees, mining process, transaction fees

per second, and security. As shown in Table 3,

there are multiple DLTs but they are still in the in-

fancy stage except blockchain that has been proven

and used widely in digital currency security (Singh

et al., 2021), which encourages its acceptance in CIs

(Georgescu and C

ırnu, 2019).

5.2.2 Recommendation

There is a big need for proposing recommended

model approaches to select the best alternative ledger

(Table 3) that can assist blockchain in case of poor

performance or security and privacy concerns, result-

ing in supporting the sustainable development of dig-

ital CIs.

5.3 Blockchain Checklists for

Designing CIs

5.3.1 Description of the Challenge

Blockchain has revolutionized decentralized software

architectures and become a fundamental building

block of CI designs. However, to date there are no

accepted laws and standards that could be followed to

unify DLTs in terms of interoperability, architecture,

and software design. There are some checklists that

can be used to facilitate the integration of blockchain

with CIs. Generally, a checklist is a strategic un-

derstanding that aims to facilitate the software devel-

opment process by efﬁciently instructing and guid-

ing developers. It has been deﬁned as (Singhal and

Uthappa, 2019): ”A comprehensive formal list of es-

sential actions to be taken in a speciﬁc fashion”. Thus,

a standard checklist can provide a detailed explana-

tion on how integrate blockchain design while foster-

ing dramatically the blockchain adoption in interde-

pendent CIs.

Due to the infancy stage of blockchain develop-

ment, there are very few studies (Table 4) that are

targeted for evaluating blockchain before its imple-

mentation. However, they have not devised a stan-

dard blockchain model that can be recommended as a

mature DLT to fulﬁll the burst CI needs effectively

and elastically. For example, a CI system may re-

quest a considerable amount of blockchain resources;

simultaneously, its demand may signiﬁcantly affect

the quality of service of its dependable CI systems.

Thus, it is necessary to provide an appropriate guide-

line on monitoring blockchain resource utilization to

fulﬁll the dynamic demands of dependable CIs. Like-

wise, the related checklist solutions have not dealt

well with the compatibility issue between private and

public blockchain transactions to ﬁt CI needs (Ghe-

orghe et al., 2018). Furthermore, they have not de-

scribed how a checklist can contribute in avoiding

or minimizing security vulnerabilities and threats of

blockchain that may cause severe consequences in

CIs, such as data leakage.

5.3.2 Recommendation

Due to the diversity of CIs and the importance of

keeping them protected against cyber-attacks (Ghe-

orghe et al., 2018), it is necessary to put forward an

institutional model for blockchain that can describe

clearly the relations between different DLTs (Table 3)

and determine in which case it is recommended to use

another DLT instead of blockchain. Furthermore, it

is necessary to collect real-world blockchain applica-

tions within different contexts to help developers to

learn how to make good use of blockchain in CI de-

signs as well as learn how to select a suitable type of

blockchain (Andreev et al., 2018), while determining

its right technical parameters for each speciﬁc CI use

case (Gheorghe et al., 2018).

Blockchain Patterns in Critical Infrastructures: Limitations and Recommendations

465

Table 4: Checklists for evaluating the implementation of Blockchain.

Paper Description

Crypto 2.0 ‘Lenses’ (Jaffrey, 2015) Develop an evaluation framework speciﬁc for the ﬁnancial applications.

Greenspan (Greenspan, 2015) Propose a general industrial framework containing eight conditions that should be veriﬁed

before the implementation of Blockchain.

METI (MET, 2017) Evaluate the comparability between conventional system and a Blockchain-based systems.

Consensus (Seibold and Samman, 2016) Propose a questionnaire for evaluating distributed consensus mechanisms.

BLOCKBENCH (Dinh et al., 2017) Propose a framework for evaluating the performance of private Blockchain components in

terms of fault-tolerance, throughput, latency, and scalability.

Case study checklist (Treiblmaier, 2020) Propose a checklist for writing Blockchain case studies.

6 CONCLUSION

In this work, we investigate the state-of-the-art lit-

erature on blockchain patterns to identify the real-

world blockchain limitations that could make bar-

riers in adopting the blockchain technology in CIs

(like transportation systems). Accordingly, a list of

lessons learned is highlighted to facilitate the fusion

of blockchain within CIs. This is followed with the

discussion of the implications and future directions of

blockchain research roadmap, following the trends of

distributed trust models, antifragile systems, check-

lists, and other alternative distributed ledger technolo-

gies.

Understanding that the use of digital technologies

is becoming a fact in our life and every digital system

is vulnerable, the management of disturbances has be-

come a top-priority concern for creating sustainable

CI systems. Thus, as a future work, we plan to assess

the degrees of blockchain criticality, and investigate

how to further advance blockchain integration within

CIs.

ACKNOWLEDGEMENTS

The work was supported from ERDF/ESF “Cy-

berSecurity, CyberCrime and Critical Informa-

tion Infrastructures Center of Excellence” (No.

CZ.02.1.01/0.0/0.0/16 019/0000822).

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