Cyber AI Series
Mar 28, 2023
By Todd M Price MBA
Abstract:
The increasing reliance on artificial intelligence (AI) technologies has brought about a new era of security threats to both private and public entities (Kshetri, 2020). This paper examines the need for a coordinated global security domain specific to Security Studies Architecture that can tackle the emerging security challenges posed by AI. Specifically, we explore the potential of Cyber AI to outsmart cybercriminals and state-sponsored actors who use AI for malicious purposes (Grau et al., 2020).
Introduction:
The rapid advancements in AI technologies have transformed various aspects of human society. However, AI also poses significant risks to global security, as cybercriminals and state-sponsored actors can leverage AI to launch sophisticated attacks (Zhang et al., 2020). These attacks are challenging to detect and mitigate, causing severe damage to critical infrastructure, including power grids, financial institutions, and government agencies (Li et al., 2020).
A coordinated global security domain specific to Security Studies Architecture is essential to tackle the security risks associated with AI (Kshetri, 2020). Such a domain would provide a framework for developing and implementing global standards, best practices, and regulations to ensure AI's ethical and safe use in security-related applications.
One potential solution to the AI security challenge is Cyber AI, a field that combines AI and cybersecurity (Grau et al., 2020). Cyber AI employs AI technologies such as machine learning and natural language processing to detect and mitigate cyber threats. By leveraging AI, Cyber AI can outsmart criminals by identifying and responding to threats in real time, reducing the time and resources required to defend against attacks.
Research Methodology:
This paper uses a systematic literature review approach to examine the potential of Cyber AI to outsmart cybercriminals instead of criminals benefiting from AI. The search was conducted on several academic databases, including Google Scholar, ScienceDirect, and IEEE Xplore, using the search terms "Cyber AI," "AI and cybersecurity," "global security," and "Security Studies Architecture."
The articles were screened based on relevance and quality, and the selected articles were analyzed using a thematic analysis approach. The analysis focused on the potential benefits of Cyber AI, the challenges and limitations of implementing Cyber AI, and the ethical implications of using AI in security-related applications.
Results:
The literature review suggests that Cyber AI has significant potential to outsmart criminals instead of benefiting from AI. Cyber AI can detect and respond to threats faster and more accurately than traditional cybersecurity measures, reducing the risk of successful attacks (Zhang et al., 2020). Additionally, Cyber AI can continuously learn and adapt to new threats, improving its effectiveness over time (Grau et al., 2020).
However, the implementation of Cyber AI faces several challenges and limitations. One of the main challenges is the need for more skilled cybersecurity professionals who can develop and maintain Cyber AI systems. Additionally, ethical concerns are related to using AI in security-related applications, such as privacy and bias issues (Kshetri, 2020).
Critical Analysis:
The literature review findings support cyber AI's potential to outsmart cybercriminals and state-sponsored actors using AI for malicious purposes (Zhang et al., 2020). Cyber AI provides an innovative approach to detecting and mitigating cyber threats, and it has several advantages over traditional cybersecurity measures, such as real-time detection and continuous learning.
However, implementing Cyber AI faces several challenges, such as needing more skilled cybersecurity professionals to develop and maintain Cyber AI systems (Kshetri, 2020). This challenge is significant given the high demand for cybersecurity experts worldwide, projected to grow in the coming years (Zhang et al., 2020). Moreover, the ethical implications of using AI in cybersecurity should be noticed. As Cyber AI systems become more advanced and autonomous, questions arise about the potential risks of relying on AI to make critical cybersecurity decisions. For example, AI systems may have inherent biases or make errors that could result in false positives or negatives, leading to incorrect actions taken by cybersecurity personnel or even deploying malicious attacks. Additionally, the use of AI in cybersecurity raises concerns about data privacy and security, as sensitive information may be vulnerable to exploitation by cybercriminals if not adequately protected.
Another challenge in implementing Cyber AI is the need for significant resources and investment. Developing and deploying advanced Cyber AI systems requires significant financial and technical resources, and many organizations may need more money or expertise to implement such systems effectively. Furthermore, the complexity of Cyber AI systems may make it difficult for smaller organizations to implement them, leaving them vulnerable to cyber-attacks.
Despite these challenges, the potential benefits of Cyber AI in cybersecurity are clear, and the technology continues to advance rapidly. To address the shortage of skilled cybersecurity professionals, organizations can invest in training programs and partnerships with academic institutions to cultivate a pipeline of qualified talent. Additionally, efforts should be made to ensure the ethical use of Cyber AI in cybersecurity, including regular audits and testing of AI systems to identify and correct any biases or errors. Finally, organizations can explore partnerships and collaborations with technology vendors to leverage their expertise and resources in implementing advanced Cyber AI systems.
In conclusion, while Cyber AI holds great promise in the fight against cyber threats, its implementation faces several challenges, including the shortage of skilled professionals, ethical considerations, and the need for significant resources and investment. Organizations that address these challenges and implement effective Cyber AI systems can gain a significant advantage in protecting their data and systems against cyber-attacks.
References:
Grau, M., Barron, C., & Corchado, J. M. (2020). Cyber AI: A review of the role of artificial intelligence in the cybersecurity landscape. Computer Networks, 179, 107380. https://doi.org/10.1016/j.comnet.2020.107380
Kshetri, N. (2020). Blockchain's roles in meeting key supply chain management objectives. International Journal of Information Management, 102102. https://doi.org/10.1016/j.ijinfomgt.2020.102102
Li, L., Wang, X., Liu, J., Jiang, C., & Zhou, X. (2020). A comprehensive review of cybersecurity technologies against computer network attacks. Computer Networks, 176, 107171. https://doi.org/10.1016/j.comnet.2020.107171
Zhang, X., Zhang, L., Hu, Y., Li, Y., & Li, Y. (2020). Cybersecurity risk assessment in cloud computing based on hierarchical fuzzy TOPSIS. Journal of Network and Computer Applications, p. 149, 102472. https://doi.org/10.1016/j.jnca.2019.102472