The impact of artificial intelligence on organisational cyber security: An outcome of a systematic literature review

Jada, Irshaad; Mayayise, Thembekile O.

doi:10.1016/j.dim.2023.100063

Cited by 8 publications

(2 citation statements)

References 57 publications

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“…It is reasonable to expect that attacks will continue to spread and adjust with improving technologies (Baisley and Cherrat, 2023;Kalutharage et al, 2023;Suhag and Daniel, 2023;Rufai et al, 2023;Pavelea and Negrea, 2024). The evolving threat landscape is projected to include integrations with Artificial Intelligence and corresponding Swarm Intelligence that botnets are capable of (Saini, M., & Budakoti, J., 2013;Owen et al, 2022;Hossain, 2023;Jada and Mayayise, 2023). These abilities would allow the botnet to utilize and share resources between running programs to emulate greater degrees of intelligence.…”

Section: Future Trends and Challengesmentioning

confidence: 99%

Botnets in Healthcare: Threats, Vulnerabilities, and Mitigation Strategies

Barnett,

Womack,

Brito

et al. 2024

eccws

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The increasing digitization of healthcare systems has introduced new opportunities to improve efficiency and accessibility for medical professionals and patients. Examples include the simplified collection, storage, and organization of patient data using electronic health records (EHRs), the use of teleconferencing software like Zoom to allow patients to meet with their care providers remotely, and medical IoT devices like glucose monitors, pacemakers, and other remote patient monitoring devices that leverage software and the internet to provide patients and their healthcare providers with critical information. All of these use cases are examples of how technology can increase the quality of patient care. While the healthcare industry has realized many benefits from its increased investment in new technology, trends have shown that this increased utilization has also opened avenues for malicious cyber actors. One of these threats is botnets. These malicious networks of compromised computers, controlled by cybercriminals, can wreak havoc on all sectors of society, with the healthcare industry proving to be a desirable target. This research is a high-level analysis that investigates the threat botnets pose by employing an exploratory review. We identify the multifaceted nature of botnet threats in healthcare, analyzing their standard forms and the vulnerabilities inherent in healthcare infrastructures, ranging from outdated software to inadequate cybersecurity protocols to poor or total lack of security awareness training for staff. Moreover, the various techniques botnets use to propagate are explored to elucidate the potential points of exploitation and the damage they can cause organizations when proper controls are not implemented. These negative consequences include data breaches, service disruptions, and compromised patient confidentiality, which can endanger medical staff and patients if not addressed. This paper then discusses proven mitigation strategies such as end-user awareness, traffic monitoring, and detection response tools that organizations can employ to reduce the potential and efficacy of such threats. The threat landscape will continue to evolve; however, by staying on top of the latest trends, we can ensure the security of such critical infrastructure and save lives.

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Section: Future Trends and Challengesmentioning

confidence: 99%

Botnets in Healthcare: Threats, Vulnerabilities, and Mitigation Strategies

Barnett,

Womack,

Brito

et al. 2024

eccws

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“…With the rapid development of technology and increasing digital integration, protecting systems and data requires advanced strategies to confront increasing cyber threats. Artificial intelligence technology is emerging as one of the most promising solutions to improve the security of systems and data, and enhance the ability to respond effectively to cyber-attacks (Jada and Mayayise, 2023).…”

Section: Introductionmentioning

confidence: 99%

The Impact of Artificial Intelligence on Cybersecurity

Ahmed

2024

IJCI

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The aim of this research is to examine the structure of the impact of AI technology on improving cybersecurity. Also, this research focuses on using machine learning and big data analysis techniques to enhance the ability to better detect and respond to cyber threats. This research follows a qualitative methodology to meet the core research objectives of assessing the impact of Artificial Intelligence on Cybersecurity by reviewing the previous studies on this field. This research focuses on using machine learning and big data analysis techniques to enhance the ability to better detect and respond to cyber threats. The comprehensive analysis of over 20 studies published between 2015-2024 offers valuable insights into the current state and impact of AI in enhancing cybersecurity policies and practices. The findings of the research revealed that artificial intelligence and machine learning significantly expand capabilities for cyber threat detection, incident alerting, and automated response through adaptive pattern recognition across diverse monitoring sources like network traffic, endpoint behaviors and security information feeds, performed at machine scale. By constantly retraining on evolving attack trends and benign usage shifts, AI holds immense potential enhancing protection. However, sizable gaps observed between touted expectations versus measured impact today highlight obstacles of practical integration like monitoring overheads, skills shortages, result interpretability, human-AI teaming dynamics, and adversarial manipulations that could undermine or reverse security aims. While transformative upside exists long-term, pragmatic roadmaps addressing these formidable challenges using best practices around responsible AI governance appear essential to maximize gains while minimizing unintended consequences of well-intentioned systems interacting with ever stealthier threats amid zones of high operational and ethical ambiguity. The research recommends using machine learning and big data analysis techniques to enhance the ability to better detect and respond to cyber threats.

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