Session
Computer Science and Communication Engineering
Description
Due to the complexity and extent of network environments, network security problems are becoming more and more serious, and network learning systems are also facing the risk of cyber security attacks. Therefore, it is necessary to design an intrusion detection system adapted for network learning systems. This system uses advanced machine learning and data mining technologies to analyze and process the data stream of the network learning system, extracting relevant features from this data stream, to build a sophisticated model of detection of intrusion detection and to realize network learning system intrusion detection. The use of intelligent algorithms increases the system's ability to effectively distinguish between normal and malicious activities. Based on research, such systems based on intelligent algorithm can achieve a high detection rate while maintaining a low false alarm rate. This balance is vital to ensure that the network learning system remains secure and stable, protecting it from intrusions and ensuring its continuous and reliable operation.
Keywords:
Network Learning Systems, Intrusion Detection, Machine Learning, Data Mining, System Stability
Proceedings Editor
Edmond Hajrizi
ISBN
978-9951-982-15-3
Location
UBT Kampus, Lipjan
Start Date
25-10-2024 9:00 AM
End Date
27-10-2024 6:00 PM
DOI
10.33107/ubt-ic.2024.386
Recommended Citation
Hoti, Liridon; Pira, Rigon; and Latifi, Dijana, "Solving Network Problems through Intelligent Systems" (2024). UBT International Conference. 2.
https://knowledgecenter.ubt-uni.net/conference/2024UBTIC/CS/2
Solving Network Problems through Intelligent Systems
UBT Kampus, Lipjan
Due to the complexity and extent of network environments, network security problems are becoming more and more serious, and network learning systems are also facing the risk of cyber security attacks. Therefore, it is necessary to design an intrusion detection system adapted for network learning systems. This system uses advanced machine learning and data mining technologies to analyze and process the data stream of the network learning system, extracting relevant features from this data stream, to build a sophisticated model of detection of intrusion detection and to realize network learning system intrusion detection. The use of intelligent algorithms increases the system's ability to effectively distinguish between normal and malicious activities. Based on research, such systems based on intelligent algorithm can achieve a high detection rate while maintaining a low false alarm rate. This balance is vital to ensure that the network learning system remains secure and stable, protecting it from intrusions and ensuring its continuous and reliable operation.