2 天前 - … of capturing and reviewing intrusion detection systems (IDS) … of research on machine
learning (ML) and deep learning (… Deep Neural Networks (DNNs) are a powerful technique …

2 天前 - … By systematically evaluating the CNN model and its deployment environment, … ,
may indicate an ongoing attack. By integrating intrusion detection systems (IDS) that analyze …

2 天前 - … Algorithm and Artificial Intelligence (PEFLID-CSAAI) technique. The primary goal
of the PEFLID-CSAAI method is to detect attack behaviors in IoT networks. The approach …

3 天前 - … Abstract: This thesis explores how artiőcial intelligence (AI) can boost … ) and
intrusion detection systems (IDS). As cyber threats become more complex, traditional security …

3 天前 - … detection systems by analyzing őrewall logs. We focus on logs from the Sophos XG
… in machine learning and deep learning, emphasizing their relevance to network security. …

3 天前 - … The core of this study involves the implementation and comparative … machine
learning techniques, including ensemble learning, deep neural networks, and anomaly detection …

3 天前 - … , offloading, caching, attack detection, geolocation, mobile … a practical arrhythmia
detection system, FL demonstrates … Taleb,“Federated deep reinforcement learning for Internet …

3 天前 - … To mitigate these vulnerabilities, intrusion detection systems (… This study systematically
utilizes various evaluation … attack for wireless security, where a deep neural network (…

5 天前 - … -system integration and engineering applications; Machine learning and deep learning
… multilayer feedforward network equipped with hidden layers, it systematically addresses …

5 天前 - … He has 34 years of teaching and research experience in coding theory, data
and network security and authentication; remote sensing and GIS-based applications, data …