Cybersecurity Testing for Cobots

Tauheed Waheed

, Eda Marchetti

and Antonello Calabr

CNR-ISTI Pisa, Italy

Keywords:

IoT, Cobots, Cybersecurity Testing, Vulnerabilities.

Abstract:

IoT (Internet of Things) rapid evolution and interconnected nature emphasize the urgent need for robust cyber-

security measures. Cybersecurity presents considerable risks and threats for the cobots (collaborative-robots)

industry. Cyber attackers can leverage these weaknesses, potentially allowing unauthorized entry and com-

promising critical assets. The proposed CTF (Cybersecurity Testing Framework) framework emerges as a

promising answer to these issues, providing an adaptable, robust, and thorough method for cobots cybersecu-

rity assurance. Understanding why cybersecurity testing is needed for cobots industry and how cobots users

interact with the system is vital, considering the changing landscape of cyber threats.CTF seeks to enhance

cobots cybersecurity by leveraging available testing suites and adhering to regulatory standards. We aim to

showcase our testing framework’s effectiveness and potential uses by depicting a speciﬁc testing strategy to

address vulnerabilities and cyber threats in cobots. The paper details the CTF theoretical foundation and criti-

cal features and presents its initial prototype to prove its suitability.

1 INTRODUCTION

Over the years, Information Technology’s (IT) role

has dramatically changed in both the social and work

sectors. Recent studies have shown that 90% of users

need an adequate level of conﬁdence in the cyberse-

curity of their IoT systems or applications (Gemalto,

2023). However, the recent advent of collaborative

robots, or cobots, in many industries has increased

the speed of this process. The collaborative robots do-

main provides an environment of working in a shared,

communal workspace with human workers to keep

building the trust of humans in technology, particu-

larly robots.

The collaborative robot is accountable for hum-

ble, repetitious duties in most applications, while a

human employee completes more complicated tasks.

Collaborative robots’ uptime, precision, and repeata-

bility improve human worker’s problem-solving skills

and intelligence.

Cobots are designed to collaborate and interact

with humans in shared workspace, transforming tra-

ditional production processes and increasing human

productivity in various industrial and commercial ar-

eas. Indeed, cobots have several beneﬁts, such as

https://orcid.org/0009-0006-0489-7697

https://orcid.org/0000-0003-4223-8036

https://orcid.org/0000-0001-5502-303X

greater productivity, adaptability, and security. In

2021, the collaborative market size comprised $701

Million, and it will increase to $2506.90 Million in

2030 at a growth rate of 15.2% as per the prognosis

period. Moreover, there is pressure to fulﬁll indus-

trial needs and explore innovative ways to carry out

massive widespread integration among various stake-

holders to resolve complex problems through collab-

orative robots.

However, when integrated into intricate cyber-

physical systems and commercial and industrial envi-

ronments, addressing the cybersecurity and trustwor-

thiness issues surrounding their use is critical. Mali-

cious actors may attempt to compromise system in-

tegrity, endanger public safety, or impede vital op-

erations by taking advantage of ﬂaws in cobot soft-

ware, communication protocols, or physical inter-

faces. Conventional cybersecurity testing techniques

might need to adequately reﬂect the complexity of

cobots-infused environments despite helping evaluate

traditional IT systems.

To address these challenges, the paper ﬁrst pro-

vides an overview of the issue and challenge of cy-

bersecurity testing in the cobots domain. It clariﬁes

the cybersecurity risks and vulnerabilities unique to

cobots, considering technical and human-centric fac-

tors. Then, it proposes a cybersecurity testing plat-

form explicitly tailored for cobots, focusing on en-

Waheed, T., Marchetti, E. and Calabrò, A.

Cybersecurity Testing for Cobots.

DOI: 10.5220/0013071000003825

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 20th International Conference on Web Information Systems and Technologies (WEBIST 2024), pages 449-456

ISBN: 978-989-758-718-4; ISSN: 2184-3252

449

hancing trustworthiness and security resilience for in-

dustrial collaboration scenarios. By integrating in-

sights from robotic experts, testers, cybersecurity an-

alysts, and cognitive psychology, the proposed plat-

form aims to bridge the gap between technical cyber-

security assessments, thereby fostering a holistic un-

derstanding of cobots trustworthiness.

Current methods ignore testing, the consequence

of cyberattacks, and affecting people’s trust in cobot

systems. Furthermore, because cobot deployments

are dynamic, proactive and adaptive testing method-

ologies are needed to react quickly to new threats

and vulnerabilities in cyber-attacks. Consequently,

it is crucial to develop specialized cybersecurity test-

ing methodology and framework suited to cobots and

their networked ecosystem.

In its exploration, the paper overviews the follow-

ing research questions (RQs):

RQ 1: Why is Cybersecurity Testing Critical for

Cobots?

Speciﬁcally, we examine the damage caused by

inadequate testing procedures for innovative tech-

nologies like cobots and the achievable mitigation

techniques.

RQ 2: What Are the Current Solutions or Frame-

works for Cobots Cybersecurity Testing?

In distinct, we scrutinize and evaluate the impact

of the lack of testing and processes on the users’

trustworthiness and cobots’ cybersecurity of prod-

ucts used by companies, organizations, ordinary

people, and governments.

RQ 3: What Are the Main Research Gaps?

We analyze current research trends in cobots cy-

bersecurity testing to recognize the signiﬁcant

gaps and guarantee the development of secure,

trustworthy, and sustainable services aligned with

social, inclusiveness, legal requirements, and eth-

ical values.

RQ 4: Which Could be a Possible Solutions?

Solutions for reducing uncertainty and increasing

overall reliability, cybersecurity and trustworthiness

must move in two technological and societal direc-

tions.

Considering the fragile nature of cybersecurity

testing, we in Section 2 have presented the current cy-

bersecurity testing strategies for cobots, and we ana-

lyze available solutions. Moreover, we have discussed

the need for cybersecurity testing for cobots in Sec-

tion 3. Then, we conceptualize and discuss our Cy-

bersecurity Testing Framework for cobots in Section

Then, Section 5 comprises of CTF architecture

and its components. Moreover, it discusses our CTF’s

workﬂow and implementation details for cobots. Fur-

thermore, the Section 6 conclusion and future work.

2 BACKGROUND AND RELATED

WORK

Human-robot collaboration (HRC) is a fascinating

ﬁeld that explores the interaction between humans

and robots as they work together to achieve shared

goals. cobots are more straightforward to program

and reconﬁgure for different tasks. Any team mem-

ber can train a cobot, making them more accessible

than traditional industrial robots, requiring special-

ized programming knowledge.

Cobot involves collaborative processes where hu-

man and robot agents cooperate to perform tasks.

These tasks span various domains, including ofﬁces,

space exploration, homes, hospitals, and manufac-

turing. Autonomous vacuum cleaners such as Whiz

(Rindﬂeisch et al., 2022) are one of the many cases

where cobots already impact various industries while

improving employee satisfaction. To position this

work in the state-of-the-art, this section provides an

overview of the main recent proposals for the cyber-

security testing of cobots.

Considering the risk-oriented approaches to as-

sessing the cybersecurity and safety of robotic sys-

tems, in (Abakumov and Kharchenko, 2023), re-

searchers proposed a robotics security methodology,

emphasizing combining various assessment tech-

niques. The testing strategies involve Penetration

Testing (PT), Faults and Vulnerabilities Injection

Testing, Risk and Vulnerabilities Assessment, Attack

Tree Analysis (ATA), and their combinations to assess

the cybersecurity and safety of robotic systems. How-

ever, it lacks an adequate testing strategy or frame-

work.

In developing a methodology for addressing secu-

rity and safety simultaneously, the embedded Man-

ufacturing Function Deployment (MFD) 4.0 de-

sign Cyber-Physical Production Systems (CPPS) and

Human-Robot Collaboration (HRC) systems within

the e Factories of the Future (FoF) (Caruana and Fran-

calanza, 2023). It focuses on innovative technologies,

comprises six steps, and includes tools like Hazard

and Risk Assessments (Saf, 2024), Morphological

Charts (Mor, 2024), and Risk Score Analysis (Kan-

dasamy et al., 2020). The testing methodology is

too generic and inadequate to prevent cyber-attacks

within Industry 5.0 and modern-day disruptive tech-

nologies.

To assess the safety of industrial robotic systems

and emphasise the importance of addressing vulnera-

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450

bilities to prevent cyberattacks and ensure safety dur-

ing operation, a proposal is presented din (Abakumov

and Kharchenko, 2022). The methodology includes

Intrusion Modes and Criticality Analysis (IMECA)

analysis with penetration testing. However, It lacks

transparent testing strategies and tools for assessing

Robotic Systems (RS) cybersecurity and safety.

As the previous proposal in the work presented in

(Abakumov and Kharchenko, 2022), penetration test-

ing is also considered an essential part of assessing

the cybersecurity and safety of industrial robotic sys-

tems. In this work, the authors focus on information

gathering, scanning, IMECA, attack, countermea-

sures selection, and reporting. The researchers rec-

ommended using tools like Wireshark (Wir, 2024),

Nmap (Nma, 2024), Metasploit (Met, 2024), and

Burp Suite Professional (Bur, 2024) to conduct pen-

etration testing. However, It lacks (Abakumov and

Kharchenko, 2022) transparent testing strategies and

tools for assessing Robotic Systems (RS) cybersecu-

rity and safety.

Considering the more generic V&V (Veriﬁcation

and Validation) process, researchers in (Kanak et al.,

2021) focus on designing, implementing, and evalu-

ating methods and tools to reduce the cost and time

of these activities. They propose automated systems

enhance safety, cybersecurity, and privacy assessment

but lack human-centricity while conducting these test-

ing activities.

The potential of cobots to work alongside humans

in the shared workspace has led to the development

of innovative solutions (Thummapudi et al., 2024) in

Industry 4.0. Finally, considering the important role

of in rising automation and enhancing productivity,

especially in Industry 5.0, the proposal of (Abishek

et al., 2023) focuses on the role of cobots in enhancing

productivity, the importance of cybersecurity, and the

potential for future advancements in manufacturing

through the integration of cobots and cybersecurity

measures. However, it is recommended to pay more

attention to cybersecurity concerns and how they con-

nect to the system’s safety. The researchers (Hollerer

et al., 2021) have conducted a security evaluation of

the Franka Emika Panda. For this particular cobot,

potential vulnerabilities have been explored and how

they could affect parameters critical to safety.

As evidenced by this overview of related work,

even if there are proposals for improving cybersecu-

rity in several application domains, there are still gaps

in the integration of cobots and cybersecurity testing

and the involvement of humans in the loop. As dis-

cussed in the rest of this paper, the evidence collected

motivates the current proposal.

Even if not exhaustive, the above examples evi-

dence that only integrated quality-control testing pro-

cess, associated with certiﬁcation procedures, guide-

lines, and round-breaking to conduct collaborative re-

search, can solve cybersecurity criticalities (Heiding

et al., 2023).

3 WHY IS CYBERSECURITY

TESTING CRITICAL FOR

COBOTS?

As highlighted in Section 2, cobots (Nahavandi,

2019) help pave the way for effective human-

robotic operations alongside humans in an interac-

tive workspace. Cybersecurity testing of cobots

refers to assessing and evaluating the security mea-

sures, vulnerabilities, and potential risks associated

with cobots. It involves thoroughly examining the

cobot systems, software, communication protocols,

and physical interfaces to identify weaknesses that

cyber-attackers or malicious actors could exploit.

Cybersecurity testing is paramount to protect or-

ganizations from cyber-attacks and ensure the con-

tinuity of their business operations. It is criti-

cal to evaluate the effectiveness of security mea-

sures(Athanasopoulos and et al., 2022; Daoudagh and

Marchetti, 2023). Furthermore, cybersecurity testing

signiﬁcantly enhances the security and reliability of

software supply chains, thereby strengthening trust in

essential software systems.

It aims to ensure data integrity, conﬁdentiality, and

availability and operations within cobot-enabled envi-

ronments. Moreover, the testing helps organizations

identify and mitigate cybersecurity threats that could

compromise the functionality of cobots, jeopardize

human safety, or lead to unauthorized access to sensi-

tive information.

Several initiatives and frameworks have been

developed and standardized, particularly OWASP’s

Software Assurance Maturity Model (SAMM,

), NIST’s Secure Software Development Frame-

work (NIST, ), ETSI’s standard 303 645 (ETSI, ),

Cybersecurity Body of Knowledge (Martin et al.,

2021) (McGraw, 2006) and Microsoft’s SDL (Mi-

crosoft, ). It is paramount to conceive and develop (by

design) quality products, which is critical to secure

innovative technologies like cobots but inadequate to

satisfy the ﬁnal requirements: building the product

right does not guarantee building the right prod-

uct (Sommerville, 2016). Testing will always remain

a pivotal strategy for human-robot trustworthiness

and cybersecurity assurance, ensuring that a product

is developed and manufactured, achieving optimum

Cybersecurity Testing for Cobots

451

Figure 1: Cybersecurity Testing.

quality.

Indeed, the lack of testing processes can affect

everyone directly or indirectly using software prod-

ucts. Moreover, companies or industrial sectors in-

volving cobots in enhancing their productivity can

be impacted by ransomware disguised as necessary

libraries or plug-ins, government organizations, and

multinationals suffering catastrophic cybersecurity at-

tacks.

Going into details, cybersecurity testing of cobots

inherits and adapts key activities typical of other ap-

plication domains such as (Lonetti and Marchetti,

2018):

Vulnerability Assessment: Cobot systems, soft-

ware, and infrastructure: it may include software

code analysis or the execution of speciﬁc testing

approaches such as access control testing, conﬁg-

uration testing, or penetration testing. This last

is widely adopted for simulating cyber attacks

and assessing the resilience of cobot systems

against real-world threats. Access control testing

is instead more focused on unauthorized access

to cobot systems.

Speciﬁcation-Based Testing: It mainly focuses on

cobot behavior and may involve the analysis of

cobot system conﬁgurations, access controls, and

security policies to ensure compliance with speci-

ﬁcations, cybersecurity best practices, and regu-

latory requirements. Speciﬁcation testing helps

identify gaps in security controls and provides

recommendations for remediation.

Threat Modeling: Threat modeling involves identi-

fying and prioritizing potential threats and attack

vectors targeting cobot systems. Organizations

can develop proactive security measures to miti-

gate the most signiﬁcant risks by analysing the ca-

pabilities and motivations of potential adversaries.

Development Lifecycle Assessment: It involves

evaluating the security practices and processes

employed during the development and deploy-

ment of cobot systems. This includes reviewing

coding standards, security testing methodologies,

and incident response procedures to ensure

that security is integrated throughout the entire

lifecycle of cobots development.

Cybersecurity testing is critical in enhancing and

evolving security measures to guarantee that cobots

operate reliably and with enhanced security. How-

ever, it is vital to maintain operational integrity and

security, with cobots indispensable in various critical

operations. Moreover, this testing is essential to for-

tify these pivotal systems against potential threats.

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Overall, cybersecurity testing of cobots is es-

sential for safeguarding the security and reliability

of cobot-enabled systems.By proactively recognizing

and addressing vulnerabilities, organizations can mit-

igate cybersecurity risks and build trust in the safety

and effectiveness of cobots technology.

In Figure 1, a schema of why cybersecuity testing

is crucial for cobots is provided to better focus on the

issue.

4 TESTING FRAMEWORK

The various domains of cybersecurity leverage ma-

jor industrial technologies such as smart manufac-

turing, the Internet of Things (IoT),cobots Artiﬁcial

Intelligence (AI),cyber-physical systems and cloud

computing, and .However, these disruptive technolo-

gies demands updated cybersecurity measures. More-

over,implementing cybersecurity testing to establish

user trustworthiness is essential.Our testing method-

ology and framework serves as a crucial direction

for protecting the environment from potential security

breaches and cyber-threats.

In the increasingly interconnected world of

cobots, it is apparent that cybersecurity measures are

crucial for managing risks and businesses, as depicted

in Figure 1. Moreover, the industry needs ethical and

proactive hackers to strengthen its defenses. Our cy-

bersecurity testing strategy also involves close col-

laboration with various stakeholders to identify and

address potential vulnerabilities and combat cyber

threats across complex and heterogeneous systems.

It has been evident from frameworks and strate-

gies presented in Section 2 that cobots lack a robust

cybersecurity testing framework. Moreover, these

frameworks do not fulﬁll the modern cybersecurity

testing needs and requirements for cobots as dis-

cussed in Section 3.Therefore, we propose developing

a cybersecurity testing framework focusing on test-

ing and resolving cybersecurity issues in the cobot

industry such as vulnerability detection. We pro-

pose a comprehensive cybersecurity testing frame-

work to protect the system from malicious actors

and enhance trustworthiness among manufacturers,

users, robotic engineers, and developers to intermedi-

ate RCDI (Robotic Code Deployment Infrastructure)

and various stakeholders as schematized in Figure 2.

Our proposed testing framework comprises of in-

terconnected layers, each representing a unique set

of components for conducting thorough cobots test-

ing. The main objective is to rediscover and en-

hance the cybersecurity measures for the collabora-

tive robots industry. Furthermore, our cybersecurity

Figure 2: Testing Framework.

testing framework can leverage cobots cybersecurity

and vulnerability issues as follows:

Software Testing: Software testing and quality as-

surance mechanisms are crucial to address cobot vul-

nerabilities. Moreover, continuous testing, stress test-

ing, security testing, usability testing, and updated

security measures are essential to minimize cobots

software-related risks.

Utilizing AI: One way to improve cobots cyberse-

curity is to substitute traditional security and pene-

tration testing methods with more advanced ones.For

example, instead of relying on penetration testing or

risk assessments, cobots can be tested using machine

learning algorithms to identify potential vulnerabil-

ities and risks frequently to be more committed to

making the testing process easier to understand and

implement through present AI/ML and LLM (Large

Language Models) techniques.

Cybersecurity Testing for Cobots

453

Figure 3: CTF Architecture.

Hybrid Testing Approach: Combining or amalga-

mating various cybersecurity testing techniques to

create a more comprehensive testing approach is cru-

cial. For instance, integrating penetration testing with

vulnerability scanning or network trafﬁc analysis can

provide a clearer picture of the cobots security threats

from a broader perspective.

Compatibility with Upgraded Infrastructure:

cobots can be integrated with newer hardware and

software technologies that improve their cyberse-

curity capabilities. For example, adding advanced

sensors and machine learning algorithms can help

cobots detect and respond to security threats more

effectively.

Innovative and Unpredictable Design: Another ap-

proach is to modify the design of the cobots to make

them more secure. It can involve using materials re-

sistant to hacking attempts or adding physical barriers

to prevent unauthorized cobot access.

Vulnerable Features: It may be possible to eliminate

security risks by removing certain features or func-

tions from the cobots. For instance, if a particular fea-

ture poses a signiﬁcant security risk, it may be worth

considering whether it is necessary for the cobots op-

eration.

5 CTF ARCHITECTURE

CTF (Cybersecurity Testing Framework) has been de-

veloped, considering security as a collaboration and a

shared responsibility among cobots developers, users,

and security professionals. Moreover, it is a testing

framework that offers an in-depth exploration of the

cybersecurity testing process for the cobots industry

from a broader perspective. It highlights the signiﬁ-

cance of cyber-attacks,recovery and resilience strate-

gies, comprehending that breaches may emerge de-

spite preventive measures claimed by cobots manu-

facturers, as discussed in our Figure 1 and Section

3.As schematized in Figure 3, CTF architecture has

the following components:

CTF Manager: The role of the CTF Manager is to

gather broader test requirements from cybersecurity

experts, cobots manufacturers, developers, penetra-

tion testers, and robotic engineers to perform effective

cybersecurity testing for cobots. Moreover, the com-

ponent also manages the various decisions made dur-

ing the testing activity execution, selecting test strate-

gies and tools. Furthermore, all these activities are

coordinated through a dedicated UI (User Interface)

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454

in CTF Manager.

Test Strategy: Test strategies provide testing tech-

niques, methods, and pre-deﬁned test cases. More-

over, it contributes to creating questionnaires utilized

by the CTF Manager. Moreover, it aligns the test-

ing process with the needs and requirements drafted

in the collected questionnaires to guarantee that the

derived test cases are sufﬁcient for cobots cybersecu-

rity testing. Furthermore, ensuring the testing process

remains adaptable and resilient to new cybersecurity

challenges and vulnerabilities in the cobots industry.

Test Generator: The purpose of the Test Generator

is to manage and validate the selection of testing strat-

egy through CTF Manager UI to generate test cases.

Moreover, the test cases are generated by considering

the speciﬁc cyber-attacks, vulnerabilities, and tools to

fulﬁll cobots testing requirements and needs. Further-

more, the component will provide a robust test suite

and help the tester select the most proﬁcient one that

aids in identifying and effectively mitigating potential

cybersecurity risks and threats for cobots.

Test Executor: The purpose of this component is to

execute the selected test cases or test suite. However,

it depends on available testing libraries and tools to

complete the test case speciﬁcation and cobots testing

execution environment (provided by the cobots man-

ufacturers or retrieved through open-source propos-

als) to execute them effectively.Furthermore, execut-

ing test cases will guarantee the seamless, conﬁden-

tiality,integrity and availability and overall cyberse-

curity of critical assets in functioning of cobots.

Test Tools: CTF integrates testing tools to conduct

testing during test execution and selection of test

strategies. However, these tools expand their pool

of resources by leveraging user feedback and test re-

ports. The components of CTF depend on this gath-

ered knowledge, enhancing the effectiveness of the

testing procedure. This component supplies adequate

resources to others, such as test strategy and test re-

sults, and helps create and design predeﬁned test case

datasets and questionnaires. Furthermore, it archives

and maintains user feedback and test reports, crucial

in optimizing testing processes for future iterations.

Results: Once test cases are executed, analyzing the

results is crucial. This analysis helps grasp the im-

plications of any vulnerabilities found and pinpoint

unnecessary pathways in RCDI, interconnected IoT

devices, and external libraries or APIs. This evalua-

tion is mostly performed through path coverage test-

ing. Moreover, the essential duty of this component is

to assess the test outcomes provided by CTF and gen-

erate test reports for users through the user interface

of the UTF manager.

To thoroughly document the results of test case

executions, it is crucial to maintain a comprehensive

report. Moreover, this report should provide a com-

prehensive traceability of the test cases conducted and

details regarding any detected vulnerabilities, where

applicable. Furthermore, it is essential to categorize

each identiﬁed vulnerability based on its severity level

and to include potential recommendations for mitigat-

ing these vulnerabilities within the report.

It’s important to understand that CTF architectural

components require cutting-edge tools and strategies

for adequate functionality. Moreover, the implemen-

tation of CTF is more focused on cobot safety and

testing it against potential cyber-attacks and vulnera-

bilities.

6 CONCLUSION

Cybersecurity is a broad domain or never-ending ar-

gument about whether it is secure or adequately se-

cure, but sincere efforts are still required to protect or-

ganizations’ critical assets. It’s crucial to understand

the need for cybersecurity testing in cobots. This

paper aims to enhance developers’ and cobots ex-

perts’ capabilities to detect vulnerabilities and counter

cyber-attacks. The CTF gives them equal opportunity

to be part of the system as testers. The critical anal-

ysis and documentation of test results play a pivotal

role in enhancing the cobots cybersecurity and efﬁ-

ciency of systems, especially in environments as com-

plex as those involving RCDI, interconnected IoT de-

vices, and external libraries or APIs. The analysis of

test results, focusing on the implications of identiﬁed

vulnerabilities and the optimization of pathways, is a

fundamental step toward ensuring the robustness and

reliability of cobots.

In the future, several improvements will be made

in CTF, particularly in integrating updated cybersecu-

rity tools that focus on a broader set of users. It is

crucial to continue advancing the methodologies and

tools used in the testing and analysis phases. Further-

more, adopting more sophisticated AI (Artiﬁcial in-

telligence) testing tools is needed to enhance the ef-

ﬁciency of test case executions and vulnerability as-

sessments. These technological advancements could

offer predictive insights into potential security threats

and suggest more proactive measures for vulnerabil-

Cybersecurity Testing for Cobots

455

ity management in cobots.

ACKNOWLEDGEMENTS

This work was partially supported by the project

RESTART (PE00000001) and the project SER-

ICS (PE00000014) under the NRRP MUR program

funded by the EU - NextGenerationEU.

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