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Abstract
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Network intrusion detection systems have become increasingly essential in protecting organizations from cyber threats and unauthorized access attempts. With organizations managing complex IT infrastructures, the continuous stream of network traffic data presents both an opportunity and a challenge for security analysts. Traditional batch-processing approaches to intrusion detection have proven inadequate in addressing the real-time requirements of modern network security, necessitating the adoption of stream mining techniques that can analyze network data as it flows through systems [The integration of data stream mining with intrusion detection systems represents a paradigm shift in how organizations approach cybersecurity, enabling them to detect suspicious activities and malicious patterns before significant damage can occur
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