Analysis of the Security and Vulnerabilities in Current UK’s Air Traffic Communication Technologies

 

 

 

2.1 Project title and timescale
Title: Analysis of the Security and Vulnerabilities in Current UK’s Air Traffic Communication Technologies

 

 

Proposed start date of data collection: December 2021
Proposed end date of data collection:  

 

 

 

 

 

2.2 Brief project description                             

 

 

 

 

 

Background

The increased growth of the global aviation industry has seen the dramatic evolution

of the business model over the last decade and airport operations (Raj and Raman, 2017; Strohmeier, 2016). Similarly, there has been diversity and traffic growth, with airline passengers having a long list of choices. These advancements have led to multiple regulatory reforms in the aviation industry by specific airline companies and supervisory agencies, including different airport governing bodies. As airports expand in parallel to establish intelligence systems and massive networks of hubs, airlines continue to perfect their operating frameworks to align growth and efficiency (Strohmeier, 2016). All these improvements create an efficient air transportation network (Gopalakrishnan et al., 2013). Airports play a vital role in economic growth and development since they are considered gateways to the world for travellers and businesses. The numerous and advanced operations within airports and airline traffic make the aviation industry characterised by advanced technological systems majorly in air traffic communication, navigation and surveillance (CNS) (Ghalem et al., 2018). The air traffic CNS equally require highly trained personnel for its operations. Therefore, the air traffic management (ATM) system is a complex global infrastructure that guarantees every aircraft’s routine maintenance and security (Yousefzadeh Aghdam et al., 2021).

The contemporary system deployed in ATM is a complex framework of intercon-

nected sub-systems made up of commercial off-the-shelf (COTS) and bespoke legacy subsystems (Ruiz et al., 2018). These sub-systems are connected through several interfaces that use proprietary, international, and national standards. Such interfaces include the airports,

 

 

incidences on ATMs. One of the widely known cyber-attack led to the shutdown of the

Federal Aviation Administration’s (FAA) ATC system in Alaska in 2006 (ASIS

International,

n.d.). Similarly, there has been a rapid rise in satellite navigation signal manipulation, where several incidences have been reported in Russian waters. Such manipulation shows water vessels, such as ships, in different locations than in reality (Burgess, 2019; BBC News, 2019). This satellite navigation signal manipulation can potentially be redirected to air traffic control signals and other global navigation satellite system (GNSS) users; thus, may result in catastrophic impacts. A wide spectrum of cyber threats have equally been targeted at air navigation service providers (ANSP) and reported by aviation stakeholders from the European ATM computer emergency response team (EATM-CERT) under

EUROCONTROL

(Harison and Zaidenberg, 2018; Istituto Affari Internazionali (IAI), 2016). The results of these cyber-attacks were mainly data theft and leakage of sensitive information such as user credentials and network schematics for sensitive aviation systems. Although the motives of such cyber-attacks may be unknown, the potential effect of these incidents are catastrophic and can cut across different ATM sub-systems.

Unfortunately, cybercriminals are inventive and have several resources to adapt to

the changing circumstances in aviation technology to exploit security vulnerabilities in the industry, such as the air traffic management (ATM) system vulnerabilities. The devastating effect of the COVID-19 on the aviation sector has further seen different cybercriminals deploy COVID-19 theme phishing lures through malicious links. Similarly, remote working— one of the key containment measures of the pandemic (Sun et al., 2021)—which is still practised by some organisations, including the aviation sector, has a significant risk of cyberattacks (Scala et al., 2021). The weak and probably unmaintained cyber threats firewalls in-home IT systems and networks can serve as cyber-attack vectors to the wider

 

ATM system. These possible security breaches prove the necessity of a holistic approach in securing the aviation industry’s technical controls and ATM process for any nation.

Therefore the economic significance of air transport and airports to the United Kingdom and the key roles

 

 

 

 

in the nation’s defence operations thus warrants an in-depth evaluation of the potential security and vulnerabilities of its current air traffic communication (ATC) technologies.

Research Aim and Objectives 

This study aims to examine the potential security and vulnerabilities in the current

UK’s air traffic management (ATM) network. The empirical research and the literature of the current study will emphasise meeting the specific objectives below:

1.      To analyse the potential exposures in current air traffic communication ATC technologies in relation to cyber attacks

2.      To understand the security knowledge and awareness of the aviation community.

3.      To develop ATC technologies security solutions that are both practical and acceptable for the aviation community.

Significance of the Study

This research will be significant as it concentrates on expanding the understanding of the most pertinent operations within the air traffic management (ATM) network by highlighting the gaps in the literature research regarding the topic. Precisely, the research is important to the UK’s Civil Aviation Authority as it will help unearth potential vulnerabilities with the organisation’s air traffic communication (ATC) technologies. The result from this study will be vital as it can be used to reduce service disruption within the aviation industry, such as delays and congestions. This research will equally be useful to different UK’s aviation stakeholders such as NATS since the information and recommendation from the study will be instrumental in sealing ATM security loopholes that could lead to severe financial losses, reputational damage, data confidentiality breaches, and other wider societal impacts.

 

 

 

 

 

 

 

 

Section 3: Research Design

 

 

 

3.1: Methodology/Methods  
Please check boxes for all methodology/methods that you plan to use:    
  Methodologies    
A Qualitative research    
B Quantitative research    
C Mixed methodology     X  
       
  Methods    
A Online questionnaires   X  
B Hand-written questionnaires   X  
C Qualitative interviews (structured, semi-structured, unstructured)   X  
D Focus groups    
E Quantitative / systematic observation    
F Qualitative non-participant observation    
G Participant observation    
H Analysis of pre-existing documents or data in a public domain    
I Analysis of pre-existing documents or data from a private source    
J Audio/video recording or photography in a public place    
K Audio/video recording or photography in a private place    
L Other method: please give details    

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3.2 Research design                                                                                                20%

 

Research Philosophy

This study will be based on the pragmatism research philosophy. In the pragmatism

research philosophy, the ability of a concept to support an action justifies its relevance. Saunders et al. (2012) underscore that, for pragmatics, multiple realities can be used in interpreting the world events, and no single perception can give the complete image of these events. Kaushik and Walsh (2019) further note that in pragmatism research philosophy, the research question can be best answered by the methods which effectively interpret them. Thus pragmatism research philosophy can accommodate quantitative and qualitative research methods. Consequently, the deployment of the mixed method in this research qualifies pragmatism as the ideal research philosophy to be deployed in the present study.

Research Method 

The choice of an ideal research method aligns with the study’s research questions and

objectives. From the objective presented above, this study will deploy a mixed research method. The mixed research method involves collecting and analysing qualitative and quantitative data (Archibald et al., 2015). Apart from linking the data at an appropriate stage, mix research method necessitates a purposeful data analysis and interpretation. Therefore, the researcher can view the phenomena under study through a wider lens and from different viewpoints. Due to the diverse nature of the research topic, a mixed-method design is ideal and justifiable for this study since it will enable the comprehensive answering of research questions that cannot singularly be addressed by either qualitative or quantitative methods (Wisdom and Creswell, 2013). Moreover, the sensitivity and technological scale of the research topic warrants the use of a mixed method since it will ensure the researcher gains a better understanding of the disparities between the quantitative and qualitative data collected from the study participants.

 
Research Data Collection 

This research will major in using primary data sources acquired through qualitative

interviews and hand-written questionnaires. Prada-Ramallal et al. (2018) note that one of the merits of deploying primary data sources in academic research is modifying the data collection approach to match a specific research objective. Specifically, the procedure in primary data collection is intended to produce the data useful for the researcher in a specific study. Paradis et al. (2016) underscore that direct data collection from primary sources improves data accuracy and the control level in the whole process. Moreover, primary data collection further provides room to accommodate various data collection methods such as interviews, surveys, and direct observation (Prada-Ramallal et al., 2018). In addition to the numerous advantages of primary data collection, the dynamic of the problem to be solved by the present study and the ever-evolving cyber threats in the aviation industry makes the adoption of primary data collection to be the ideal approach. Precisely, the use of secondary data in the present study may be irrelevant due to outdated cyber threats and cyber-criminal activities, thus leading to irrelevant references in the contemporary aviation industry.

Population and Sampling 

Both quantitative and qualitative data will be collected through structured interviews and questionnaires from a private pilot, commercial pilot, civil ATC, aviation engineer, aviation authority, IT engineers, data protection engineers, and other relevant stakeholders in the aviation UK aviation sector. The study will use purposive sampling. Purposive sampling has been defined as selecting participants according to the set criteria of the study (Ames et al., 2019). Thus, the set criteria in the present study involve the use of key players in the UK aviation sector.

 

 

 

 

                         

 

 

 

3.3 Ethical implications                                                                                            10%
 

The key role of air traffic control in the UK and the global aviation industry makes

analysing its vulnerabilities a sensitive topic in aeronautics research. Therefore, the present study recognises the delicate nature of its topic and key objectives as it can reveal potentially exploitable flaws in the industry. However, although the present study will focus on the current UK’s air traffic communication technological vulnerabilities, some of the key elements of air traffic control and management have been extensively researched by scholars and hacker communities and are in the public domain. The inherent vulnerability of these security protocols have been widely researched for decades, and more in-depth analysis done with reports have been published regarding these security loopholes.

Therefore, the present study only aims to expound on the already existing information to the relevant aviation authorities. As such, the ultimate goal of the present study is to increase awareness of the current state in the aviation industry since the researcher believes that awareness creation is one of the key security pillars of future air traffic management technologies. Certainly, the researcher believes that apart from the wide research currently witnessed in the aviation industry, there is a great change in perception within the aviation circles.

The present study will adhere to the responsible information disclosure procedure of its results to the relevant air traffic management firms and will constantly update the relevant management of its security standards regarding the study’s data integrity. Lastly, the potential challenge envisaged in the present study will be the unwillingness of certain participants to disclose their specific air traffic technology protocols due to the company’s operating procedures and safety standards. Such occurrences may lead to the collection of incomplete data, which can further result in making inadequate or biased inferences from the study.

 

 

 

 

 

Section 4: Participants and Recruitment

 

 

 

Section 4.1: Participants (eg interviewees)
The main participants to be recruited for the research will be relevant stakeholders in UK’s aviation sector. Precisely, the study participants will include private pilots, commercial pilots, civil ATCs, aviation engineers, aviation authorities, military pilots, military ATCs, and other key players ATM. The main inclusion criteria for the participant recruitment process will include:

The participant must be a relevant expert in the aviation industry

The participant must have sufficient experience in the industry (preferably more than 3 years of experience in the aviation sector)

The participant must have relevant licenses to operate in the aviation industry within

the UK’ jurisdiction

The participant must agree to take part in the study through the signing of a consent form.

 

Section 4.2: Recruitment method
Potential study participants will be approached through LinkedIn. Below is a brief outline of how potential participants will be approached and recruited into the project through the professional networking platform:

1.      The researcher will upgrade their linked in account to obtain the LinkedIn recruiter license

2.      Under the LinkedIn project tab, the researcher will update key details of the research project

  1. The researcher will use the inclusion criteria highlighted in section 4.1 above to search for potential participants in the LinkedIn talent pool and search tab
  2. The researcher will review and shortlist anyone they consider relevant for the study from the filtered candidates by the inclusion criteria.
  3. Finally, the researcher will write messages and send them to the potential shortlisted participants highlighting key project details (including start and end dates), and wait for their response

 

 

Section 5: Consent procedure
This section will demonstrate how you will obtain informed consent from the participants. Please include all supporting documents (eg Information Sheets, Consent forms and questionnaires). Please answer YES, NO or NOT APPLICABLE (N/A) to each of the following:
  Yes No N/A
5.1 All respondents will be given an Information Sheet and enough time to read it before being asked to agree to participate. X    
5.2 All participants taking part in an interview, focus group, observation (or other activity which is not questionnaire-based) will be asked to sign a consent form. X    
5.3 All participants completing a questionnaire will be informed on the Information Sheet that returning the completed questionnaire implies consent to participate. X    
5.4 All participants being asked to provide sensitive personal data will have the following statement on the consent form or on the bottom of their questionnaire “I consent to the processing of my personal information for the purposes of this research study. I understand that such information will be treated as strictly confidential and handled in accordance with the UK Data Protection legislation’’. A tick box should be included to allow participants to give explicit consent for the collection and use of such data. X    
5.5 All respondents will be told that they can withdraw at any time, ask for their interview recording to be destroyed and/or their data removed from the project until it is no longer practical to do so (e.g. when the report has been written up). X    
5.6 Where full information cannot be given prior to participation (because it could influence outcomes) participants will be fully debriefed after participation. X    
5.7 If you answered NO to any of the above (or think more information could be useful to the reviewer) please state why here:

 

 

 

Section 6: Confidentiality, Anonymity & Data and Records Management
This section will show how participants can expect confidentiality and/or anonymity and will show how any research data collected will be managed during and after the study. Confidential data is not disclosed to other people; Anonymous data cannot be linked to the participant’s personal details.

Please answer YES, NO or NOT APPLICABLE (N/A) to each of the following:

  Yes No N/A
6.1 Questionnaires will be returned anonymously and indirectly. (eg via a web link) Please note that questionnaire data cannot then be followed up/clarified. X    
6.2 Questionnaires and/or interview transcripts will only be identifiable by a unique identifier (e.g. code/pseudonym) X    
6.3 Lists of identity number or pseudonyms linked to names and/or addresses will be stored securely and separately from research data X    
6.4 All place names and institutions which could lead to the identification of individuals or organisations will be changed X    
6.5 I confirm that all processing of personal information related to the study will be in full compliance with the General Data Protection Regulation (GDPR) X    
6.6 If you answered NO to any of the above (or think more information could be useful to the reviewer) please state why here:

 

 

 

 

 

 

 

Up to this point, from the start of this document, your word count when complete should be between 2700 and 3200 words ALTOGETHER, including all text already in the document!

 

 

 

 

Section 7: Reference list                                                                                          (10%)  

 

 

Ames, H., Glenton, C. and Lewin, S., 2019. Purposive sampling in a qualitative evidence syn-

thesis: A worked example from a synthesis on parental perceptions of vaccination communication. BMC medical research methodology, 19(1), pp.1-9.

Archibald, M. M., Radil, A. I., Zhang, X., & Hanson, W. E. (2015). Current mixed methods

practices in qualitative research: A content analysis of leading journals. International

Journal of Qualitative Methods, 14(2), 5–33. https://doi.org/10.1177/160940691501400205  

ASIS International. (n.d.). Dept. Of transportation: Air traffic control systems have been

hacked. Retrieved November 15, 2021, from https://www.asisonline.org/securitymanagementmagazine/articles/2009/05/dept.oftransportationairtrafficcontrolsystemshavebeenhacked/ 

BBC News., 2019. Study maps “extensive Russian GPS spoofing.” Retrieved November 15,

2021, from https://www.bbc.com/news/technology47786248 

Burgess, M., 2019. To protect Putin, Russia is spoofing GPS signals on a massive scale.

WIRED UK. Retrieved November 15, 2021, from https://www.wired.co.uk/article/russiagpsspoofing 

EUROCONTROL., 2021. Network operations. Retrieved November 15, 2021, from

https://www.eurocontrol.int/networkoperations 

Fox, S. J., 2016. Flying challenges for the future: Aviation preparedness – in the face of cyber-

terrorism. Journal of Transportation Security, 9(3–4), 191–218.

https://doi.org/10.1007/s1219801601741 

Ghalem, Â., Okar, C., Chroqui, R., & Semma, E., 2018. Air traffic management performance

framework case study: Morocco. IFAC-PapersOnLine, 51(11), 1–6.

https://doi.org/10.1016/j.ifacol.2018.08.225 

Gopalakrishnan, K., Govindarasu, M., W. Jacobson, D., & M. Phares, B., 2013. Cyber security

for airports. International journal for traffic and transport engineering, 3(4), 365–376.

https://doi.org/10.7708/ijtte.2013.3(4).02 

 

Harison, E., & Zaidenberg, N., 2018. Survey of cyber threats in air traffic control and aircraft

communications systems. Cyber Security: Power and Technology, 199–217.

https://doi.org/10.1007/9783319753072_12 

Istituto Affari Internazionali (IAI)., 2016. The defence of civilian air traffic systems from cyber

threats.

Kaushik, V., & Walsh, C. A., 2019. Pragmatism as a research paradigm and its implications

for social work research. Social Sciences, 8(9), 255.

https://doi.org/10.3390/socsci8090255 

Lampa, G., 2020. AIR TRAFFIC MANAGEMENT: A CYBERSECURITY CHALLENGE.

Transport Security International Magazine. Retrieved November 15, 2021, from https://www.tsimag.com/airtrafficmanagementacybersecuritychallenge/ 

Nobles, C., 2017. Cyber Threats in Civil Aviation. Security Solutions for Hyperconnectivity

and the Internet of Things, 272–301. https://doi.org/10.4018/9781522507413.ch011 

Paradis, E., O’Brien, B., Nimmon, L., Bandiera, G. and Martimianakis, M. A. T., 2016. De-

sign: selection of data collection methods. Journal of Graduate Medical Education,

8(2), 263–264. https://doi.org/10.4300/jgmed1600098.1  

Prada-Ramallal, G., Roque, F., Herdeiro, M. T., Takkouche, B. and Figueiras, A., 2018. Pri-

mary versus secondary source of data in observational studies and heterogeneity in meta-analyses of drug effects: A survey of major medical journals. BMC Medical

Research Methodology, 18(1), 1. https://doi.org/10.1186/s1287401805613  

Raj, P. and Raman, A.C., 2017. The Internet of Things: Enabling technologies, platforms, and

use cases. CRC Press.

Ruiz, S., Lopez Leones, J., & Ranieri, A., 2018. A novel performance framework and method-

ology to analyse the impact of 4D trajectory based operations in the future air traffic management system. Journal of Advanced Transportation, 2018, 1–17.

https://doi.org/10.1155/2018/1601295 

Saunders, M., Lewis, P. & Thornhill, A., 2012. “Research Methods for Business Students”

6th edition, Pearson Education Limited

Scala, P., Mujica Mota, M., & Delahaye, D., 2021. Air traffic management during rare events

such as a pandemic: Paris charles de gaulle case study. Aerospace, 8(6), 155.

https://doi.org/10.3390/aerospace8060155 

Strohmeier, M., 2016. Security in next generation air traffic communication networks (Doc-

toral dissertation, University of Oxford).

Sun, X., Wandelt, S., Zheng, C., & Zhang, A., 2021. COVID-19 pandemic and air transporta-

tion: Successfully navigating the paper hurricane. Journal of Air Transport

Management, 94, 102062. https://doi.org/10.1016/j.jairtraman.2021.102062 

Wisdom, J. and Creswell, J.W., 2013. Mixed methods: integrating quantitative and qualitative

data collection and analysis while studying patient-centered medical home models.

Rockville: Agency for Healthcare Research and Quality.

Yousefzadeh Aghdam, M., Kamel Tabbakh, S. R., Mahdavi Chabok, S. J., & Kheyrabadi, M., 2021. Optimisation of air traffic management efficiency based on deep learning enriched by the long short-term memory (LSTM) and extreme learning machine (ELM).

Journal of Big Data, 8(1), 1. https://doi.org/10.1186/s40537021004386  

 

 

 

 

 

 

 

 

 

 

 

 

Section 8: Checklist for Applicant

 This form

The Participant Information Sheet (If you wish)

The Consent Form (If you wish)

Materials for recruitment of participants (If you wish)

 

 

 

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