Improving Security of Business Intelligent Systems with AI and Machine Learning
Business Intelligence (BI) systems evaluate and transform raw data into meaningful insights to support strategic decision-making. As cyber-threats advance, BI Systems Continues to face severe challenges in safeguarding valuable assets. The integration of artificial intelligence (AI) and Machine Learning (ML) Technologies emerges as an ideal optimism with advanced technologies to outsmart cybercriminals. This paper examined the important role of AI and ML in improving the security of BI systems. The paper focused on investigating efficiency in threat detection, identification of anomalies, automated response, and predictive analysis. The study employed AI, and ML threat detection strategies in real-time, identifying potential attacks, similarly enhancing threat detection using ML to expose possible hidden threats within BI systems. The paper investigates the importance of securing BI sensitive data highlighting the continuous learning and improvement mechanisms employed. Finally, the paper provides a comprehensive analysis on Security of BI Systems and a systematic review emphasizing the critical need for continuous adaptation and collaboration to stay ahead of cyber threats safeguarding vital business insights.
Authors
- Daniel Dauda Wisdom
- Joshua Bature Hassan
- Odunayo Esther Oduntan
- Olufunke Rebecca Vincent (ORCID: https://orcid.org/0000-0002-6196-4183)
- Taiwo Olufemi Ajayi
- Cathrine Febisola Falayi
Institutions
- Federal University of Agriculture, Abeokuta (NG)
- The Federal Polytechnic, Ado-Ekiti (NG)
- Federal University Oye Ekiti (NG)
Publication Details
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1109/smartblock4africa61928.2024.10779496
- Citations
- 2
- Primary Topic
- Economic and Technological Systems Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.46