Cyber-risk Mitigation Strategies and the Role of Artificial Intelligence in Mitigating Cyber-Risks: The Case of the United Arab Emirates Transport Sector
The scale, volume, and sophistication levels of cyber-risks and threats to critical services and infrastructures of nations are surpassing defensive procedures and measures put in place. Destructive and disruptive cyber activities require the UAE government to address and invest in making the countr...
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2025
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| Online Access: | https://bspace.buid.ac.ae/handle/1234/2920 |
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| _version_ | 1862980620860260352 |
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| author | ALYAMMAHI, ALI SAEED ALI AHMED |
| author_facet | ALYAMMAHI, ALI SAEED ALI AHMED |
| author_role | author |
| dc.contributor.none.fl_str_mv | Professor Edward Ochieng |
| dc.creator.none.fl_str_mv | ALYAMMAHI, ALI SAEED ALI AHMED |
| dc.date.none.fl_str_mv | 2025-05-05T10:57:15Z 2025-05-05T10:57:15Z 2025-04 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | 20171131 https://bspace.buid.ac.ae/handle/1234/2920 |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | The British University in Dubai (BUiD) |
| dc.subject.none.fl_str_mv | cybersecurity, cyber-risk mitigation, Artificial intelligence (AI), Machine Learning (ML), Deep Learning (DL), cyber-risk mitigation model, strategies and processes |
| dc.title.none.fl_str_mv | Cyber-risk Mitigation Strategies and the Role of Artificial Intelligence in Mitigating Cyber-Risks: The Case of the United Arab Emirates Transport Sector |
| dc.type.none.fl_str_mv | Thesis |
| description | The scale, volume, and sophistication levels of cyber-risks and threats to critical services and infrastructures of nations are surpassing defensive procedures and measures put in place. Destructive and disruptive cyber activities require the UAE government to address and invest in making the country move from a state of cyber insecurity to a state of cyber readiness. Losses are accumulating, the damage is growing and the danger to critical infrastructure assets is imminent. Critical infrastructures are physical structures and systems whose unavailability compromises the maintenance of services or resources of a locality, region or country. Critical infrastructures related to airport, sea power, traffic management and navigation systems, networks, vehicles and others can be the target of different cyber-attacks for different reasons. This research aimed to highlight the importance of building agile and resilient cybersecurity systems that can address emerging cyber-risks. The research employed a quantitative method, a survey questionnaire, which was completed by 286 participants. The key research findings based on the theoretical and practical data showed that there is a significant relationship between cybersecurity considerations and cyber-risk mitigation and also there is a significant relationship between employing artificial intelligence (AI) adoption and cyber-risk mitigation. The research findings emphasised the key role of leadership in steering the cybersecurity posture in terms of spreading a healthy cybersecurity culture within transport organisations, as it has a significant impact on preventing vulnerabilities and adopting smart technologies such as artificial intelligence and machine learning. Raising staff awareness about different cyber-risks, hygiene practices, and behavioural and attitude change play a key role in preventing and managing cyber-risks. |
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| identifier_str_mv | 20171131 |
| language_invalid_str_mv | en |
| network_acronym_str | budr |
| network_name_str | The British University in Dubai repository |
| oai_identifier_str | oai:bspace.buid.ac.ae:1234/2920 |
| publishDate | 2025 |
| publisher.none.fl_str_mv | The British University in Dubai (BUiD) |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Cyber-risk Mitigation Strategies and the Role of Artificial Intelligence in Mitigating Cyber-Risks: The Case of the United Arab Emirates Transport SectorALYAMMAHI, ALI SAEED ALI AHMEDcybersecurity, cyber-risk mitigation, Artificial intelligence (AI), Machine Learning (ML), Deep Learning (DL), cyber-risk mitigation model, strategies and processesThe scale, volume, and sophistication levels of cyber-risks and threats to critical services and infrastructures of nations are surpassing defensive procedures and measures put in place. Destructive and disruptive cyber activities require the UAE government to address and invest in making the country move from a state of cyber insecurity to a state of cyber readiness. Losses are accumulating, the damage is growing and the danger to critical infrastructure assets is imminent. Critical infrastructures are physical structures and systems whose unavailability compromises the maintenance of services or resources of a locality, region or country. Critical infrastructures related to airport, sea power, traffic management and navigation systems, networks, vehicles and others can be the target of different cyber-attacks for different reasons. This research aimed to highlight the importance of building agile and resilient cybersecurity systems that can address emerging cyber-risks. The research employed a quantitative method, a survey questionnaire, which was completed by 286 participants. The key research findings based on the theoretical and practical data showed that there is a significant relationship between cybersecurity considerations and cyber-risk mitigation and also there is a significant relationship between employing artificial intelligence (AI) adoption and cyber-risk mitigation. The research findings emphasised the key role of leadership in steering the cybersecurity posture in terms of spreading a healthy cybersecurity culture within transport organisations, as it has a significant impact on preventing vulnerabilities and adopting smart technologies such as artificial intelligence and machine learning. Raising staff awareness about different cyber-risks, hygiene practices, and behavioural and attitude change play a key role in preventing and managing cyber-risks.The British University in Dubai (BUiD)Professor Edward Ochieng2025-05-05T10:57:15Z2025-05-05T10:57:15Z2025-04Thesisapplication/pdf20171131https://bspace.buid.ac.ae/handle/1234/2920enoai:bspace.buid.ac.ae:1234/29202025-07-18T08:03:58Z |
| spellingShingle | Cyber-risk Mitigation Strategies and the Role of Artificial Intelligence in Mitigating Cyber-Risks: The Case of the United Arab Emirates Transport Sector ALYAMMAHI, ALI SAEED ALI AHMED cybersecurity, cyber-risk mitigation, Artificial intelligence (AI), Machine Learning (ML), Deep Learning (DL), cyber-risk mitigation model, strategies and processes |
| title | Cyber-risk Mitigation Strategies and the Role of Artificial Intelligence in Mitigating Cyber-Risks: The Case of the United Arab Emirates Transport Sector |
| title_full | Cyber-risk Mitigation Strategies and the Role of Artificial Intelligence in Mitigating Cyber-Risks: The Case of the United Arab Emirates Transport Sector |
| title_fullStr | Cyber-risk Mitigation Strategies and the Role of Artificial Intelligence in Mitigating Cyber-Risks: The Case of the United Arab Emirates Transport Sector |
| title_full_unstemmed | Cyber-risk Mitigation Strategies and the Role of Artificial Intelligence in Mitigating Cyber-Risks: The Case of the United Arab Emirates Transport Sector |
| title_short | Cyber-risk Mitigation Strategies and the Role of Artificial Intelligence in Mitigating Cyber-Risks: The Case of the United Arab Emirates Transport Sector |
| title_sort | Cyber-risk Mitigation Strategies and the Role of Artificial Intelligence in Mitigating Cyber-Risks: The Case of the United Arab Emirates Transport Sector |
| topic | cybersecurity, cyber-risk mitigation, Artificial intelligence (AI), Machine Learning (ML), Deep Learning (DL), cyber-risk mitigation model, strategies and processes |
| url | https://bspace.buid.ac.ae/handle/1234/2920 |