Natural language processing frameworks for real-time decision-making in cybersecurity and business analytics

Blessing Austin-Gabriel 1, *, Nurudeen Yemi Hussain 2, Adebimpe Bolatito Ige 3, Peter Adeyemo Adepoju 4 and Adeoye Idowu Afolabi 5

1 Independent Researcher, NJ, USA.
2 Independent Researcher, Texas USA.
3 Independent Researcher, Canada.
4 Independent Researcher, UK.
5 Independent Researcher, Nigeria.
 
Review
International Journal of Science and Technology Research Archive, 2023, 04(02), 086-095.
Article DOI: 10.53771/ijstra.2023.4.2.0018
Publication history: 
Received on 12 January 2023; revised on 10 June 2023; accepted on 14 June 2023
 
Abstract: 
Natural Language Processing (NLP) has emerged as a transformative technology, enabling real-time decision-making in critical cybersecurity and business analytics domains. This paper explores the theoretical foundations of NLP, emphasizing its ability to process unstructured data and deliver actionable insights at scale. Key applications in cybersecurity include detecting phishing attempts, malware, and anomalies, where NLP frameworks enhance threat identification and response times. In business analytics, NLP facilitates sentiment analysis, customer feedback processing, and trend forecasting, driving data-driven decision-making and improving customer experiences. Despite its immense potential, challenges such as false positives, adversarial attacks, scalability, domain-specific language adaptation, and ethical concerns remain significant hurdles. To address these, the paper recommends refining model accuracy, enhancing robustness against attacks, and adopting scalable and ethical approaches for business analytics applications. By advancing NLP frameworks, organizations can better navigate the complexities of real-time decision-making, ensuring operational efficiency and strategic success in dynamic environments.

 

Keywords: 
Natural Language Processing (NLP); Real-Time Decision-Making; Cybersecurity Applications; Business Analytics; Ethical Data Processing
 
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