Transparent Peer Review By Scholar9
The Role of AI in Strengthening Cybersecurity: Promise and Risks
Abstract
Artificial Intelligence (AI) is increasingly playing a critical role in bolstering cybersecurity, offering capabilities that can revolutionize how organizations detect, prevent, and respond to cyber threats. AI-driven solutions, such as machine learning (ML) models, can process vast amounts of data at unprecedented speeds, identifying patterns and anomalies that human analysts might overlook. These systems enhance threat detection through techniques like anomaly detection, behavioural analysis, and predictive analytics, enabling quicker and more efficient identification of sophisticated attacks, such as Advanced Persistent Threats (APTs). Additionally, AI facilitates automated incident response, reducing the time between detection and mitigation, which is crucial in minimizing damage from cyberattacks. However, while AI strengthens cybersecurity, it also introduces new vulnerabilities. Adversarial attacks, such as data poisoning and model evasion, are emerging threats where attackers manipulate AI models to bypass security defences or produce erroneous outputs. Moreover, cybercriminals are leveraging AI to develop more sophisticated malware, phishing attacks, and social engineering tactics. The dual use of AI by defenders and attackers creates a constant arms race in cybersecurity, necessitating robust frameworks to secure AI systems themselves. This paper explores the transformative impact of AI on cybersecurity, analysing its potential benefits and the emerging risks associated with its deployment. By examining both defensive applications and the growing threat landscape, this study underscores the need for an adaptive and secure AI infrastructure in cybersecurity, ensuring that as AI evolves, it remains a force for enhancing digital security without amplifying risks.
Chandrasekhara (Samba) Mokkapati Reviewer
24 Sep 2024 05:38 PM
Not Approved
Relevance and Originality
This paper effectively addresses the vital role of Artificial Intelligence (AI) in enhancing cybersecurity, particularly in the context of rapidly evolving cyber threats. By focusing on how AI technologies transform threat detection, prevention, and response, the research presents original contributions to an urgent area of study. The dual exploration of both the benefits and challenges associated with AI integration in cybersecurity provides valuable insights relevant to both practitioners and researchers.
Methodology
The methodology section should clearly outline the research design adopted, whether qualitative, quantitative, or mixed methods. It would be beneficial to specify the sources of data—such as case studies, surveys, or empirical research—and explain the rationale behind their selection. Additionally, detailing the analytical approaches used to interpret the data will enhance the credibility of the findings and provide a clear framework for understanding the research process.
Validity & Reliability
To bolster the validity of the findings, the paper should discuss how the results were cross-validated, potentially through comparisons with existing literature or expert interviews. Addressing the reliability of the data collection methods and any tools used will further support the study's credibility. It would also be helpful to acknowledge any limitations faced during the research process, such as sample bias or data constraints, to provide a comprehensive understanding of the findings' applicability.
Clarity and Structure
The paper should be organized into distinct sections, including an introduction, methodology, results, and discussion, with each section clearly labeled for easy navigation. A logical flow between sections will enhance reader comprehension. Ensuring that the language is clear and accessible, while avoiding excessive technical jargon, will allow a wider audience to engage with the critical issues related to AI in cybersecurity.
Result Analysis
The analysis should provide a deeper examination of how AI technologies contribute to more effective threat detection and incident response, comparing these methods to traditional approaches to illustrate tangible benefits. Additionally, a thorough exploration of the new vulnerabilities introduced by AI, such as adversarial attacks, is essential for offering a balanced view. This discussion will inform future research and help establish guidelines for developing secure AI frameworks in cybersecurity, ensuring that advancements in AI do not exacerbate existing risks.
IJ Publication Publisher
Done Sir
Chandrasekhara (Samba) Mokkapati Reviewer