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Zaki Firli, Muhammad
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Advanced Cyber Threat Detection: Big Data-Driven AI Solutions in Complex Networks Rizky, Agung; Zaki Firli, Muhammad; Aulia Lindzani, Nur; Audiah, Sipah; Pasha, Lukita
CORISINTA Vol 1 No 2 (2024): August
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v1i2.42

Abstract

In the rapidly evolving digital landscape, cybersecurity has become increasingly critical, especially within complex network environments. This research presents the development of a cyber threat detection system that leverages Artificial Intelligence (AI) and Big Data analytics to enhance accuracy and speed in identifying and responding to cyber threats. The system was evaluated through rigorous testing, demonstrating a high detection accuracy of 95\% for malware and unauthorized access attempts, along with an impressive detection speed of 2 seconds on average for most threats. Additionally, the system exhibited strong scalability, maintaining optimal performance even with increasing network complexity. These findings underscore the system's robustness and practical applicability in real-world scenarios. However, further refinement is suggested to improve anomaly detection and reduce response times for more complex threats. This study contributes valuable insights into the integration of AI and Big Data in cybersecurity, providing a scalable and effective solution for protecting critical network infrastructures.
Co-Authors Audiah, Sipah Aulia Lindzani, Nur Pasha, Lukita Rizky, Agung