Cybersecurity alerts and advisories: Leveraging artificial intelligence to secure digital assets

被引:0
作者
Malatji, Masike [1 ]
机构
[1] Univ South Africa UNISA, Grad Sch Business Leadership SBL, Digital Transformat & Value Chain Management, Johannesburg, South Africa
来源
2024 IEEE TECHNOLOGY AND ENGINEERING MANAGEMENT SOCIETY, TEMSCON LATAM 2024 | 2024年
关键词
Artificial Intelligence; Cybersecurity Alerts/Advisories; Mitigation Strategies; Sector-specific Vulnerabilities; Threat Analysis; Predictive Analytics;
D O I
10.1109/TEMSCONLATAM61834.2024.10717777
中图分类号
学科分类号
摘要
This paper analyses cybersecurity alerts and advisories issued by the Cybersecurity and Infrastructure Security Agency of the United States of America from January 2023 to March 2024. Employing a qualitative content analysis methodology, the study investigates prevalent cyber threats, identifies the most impacted industry sectors and affected systems, and evaluates recommended mitigation strategies. The analysis categorises the identified threats, revealing sector-specific vulnerabilities and their impact on critical systems. Furthermore, the study explores the potential of Artificial Intelligence (AI) to enhance cybersecurity practices. Key findings highlight significant trends in ransomware attacks, phishing campaigns, state-sponsored activities, and vulnerabilities within critical infrastructure, underlining the crucial need for robust cybersecurity solutions. The paper recommends integrating AI into existing cybersecurity frameworks, enhancing predictive threat detection capabilities, automating response systems, and improving network behavioural analytics. While acknowledging the valuable insights from public advisories, the study also identifies their limitations. Finally, the paper suggests potential avenues for future research to further refine cybersecurity strategies and policies.
引用
收藏
页数:7
相关论文
共 37 条
[1]   A holistic and proactive approach to forecasting cyber threats [J].
Almahmoud, Zaid ;
Yoo, Paul D. ;
Alhussein, Omar ;
Farhat, Ilyas ;
Damiani, Ernesto .
SCIENTIFIC REPORTS, 2023, 13 (01)
[2]   Improving Threat Mitigation Through a Cybersecurity Risk Management Framework: A Computational Design Science Approach [J].
Ampel, Benjamin M. ;
Samtani, Sagar ;
Zhu, Hongyi ;
Chen, Hsinchun ;
Nunamaker, Jay F. .
JOURNAL OF MANAGEMENT INFORMATION SYSTEMS, 2024, 41 (01) :236-265
[3]  
[Anonymous], [43] 14:00-17:00, "ISO 10993-1:2018," ISO. Accessed: Apr. 18, 2024. [Online]. Available: https://www.iso.org/standard/68936.html
[4]  
[Anonymous], 188. Centers for Disease Control and Prevention Disease Burden of Flu Available online: https://www.cdc.gov/flu/about/burden/index.html(accessed on Jun 14, 2023).
[5]  
Arshey M., 2021, 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), P353, DOI 10.1109/ICACCS51430.2021.9441925
[6]   A comprehensive survey of AI-enabled phishing attacks detection techniques [J].
Basit, Abdul ;
Zafar, Maham ;
Liu, Xuan ;
Javed, Abdul Rehman ;
Jalil, Zunera ;
Kifayat, Kashif .
TELECOMMUNICATION SYSTEMS, 2021, 76 (01) :139-154
[7]  
Camacho N. G., 2024, J. Artif. Intell. Gen. Sci. JAIGS ISSN3006-4023, V1
[8]   Explainable Artificial Intelligence in CyberSecurity: A Survey [J].
Capuano, Nicola ;
Fenza, Giuseppe ;
Loia, Vincenzo ;
Stanzione, Claudio .
IEEE ACCESS, 2022, 10 :93575-93600
[9]   Artificial Intelligence in Cybersecurity: The Use of AI Along the Cyber Kill Chain [J].
Chomiak-Orsa, Iwona ;
Rot, Artur ;
Blaicke, Bartosz .
COMPUTATIONAL COLLECTIVE INTELLIGENCE, PT II, 2019, 11684 :406-416
[10]  
CISA, Cybersecurity alerts & advisories | CISA'