Add to ORKGPresented herein are techniques for correlating the output of a crowd counting machine learning (ML) algorithm, which operates on surveillance video, with observed network load to determine if a load spike is due to a valid network usage or an attacker trying to sabotage the network. The techniques presented herein include vision field classification based on access point (AP) coverage, linking of vision fields to AP coverage in DNAC UI, and consensus-based threat assessment and alerts
A novel Machine Learning (ML) method based on Neural Networks (NN) is proposed to assess radio-frequ...
This study proposes using machine learning to improve Wi-Fi network security. As Wi-Fi networks spre...
The landscape of network analysis is ever-evolving as the fields of technology and business progress...
Using machine learning (ML) to make observations of network operations is faced with many constraint...
Few years back the number of wireless devices and their use in our daily life has been increased a l...
This research examines the use of machine-learning techniques to identify malicious traffic in an em...
This thesis addresses the topic of development and advancement of the wireless technology. Report de...
This paper proposes an anomaly detection framework that utilizes key performance indicators (KPIs) a...
Presented herein are innovative techniques for analyzing network traffic and identifying anomalous p...
This paper examined the impact of a network attack on a congested transmission session. The research...
This paper examined the impact of a network attack on a congested transmission session. The research...
Network Security Management is not only becoming difficult but also becoming impossible as size of n...
This paper examined the impact of a network attack on a congested transmission session. The research...
Most examples that lead to communication and deception indicate our plans to maximize the use of low...
Machine learning plays a vital role in understanding threats, vulnerabilities, and security policies...
A novel Machine Learning (ML) method based on Neural Networks (NN) is proposed to assess radio-frequ...
This study proposes using machine learning to improve Wi-Fi network security. As Wi-Fi networks spre...
The landscape of network analysis is ever-evolving as the fields of technology and business progress...
Using machine learning (ML) to make observations of network operations is faced with many constraint...
Few years back the number of wireless devices and their use in our daily life has been increased a l...
This research examines the use of machine-learning techniques to identify malicious traffic in an em...
This thesis addresses the topic of development and advancement of the wireless technology. Report de...
This paper proposes an anomaly detection framework that utilizes key performance indicators (KPIs) a...
Presented herein are innovative techniques for analyzing network traffic and identifying anomalous p...
This paper examined the impact of a network attack on a congested transmission session. The research...
This paper examined the impact of a network attack on a congested transmission session. The research...
Network Security Management is not only becoming difficult but also becoming impossible as size of n...
This paper examined the impact of a network attack on a congested transmission session. The research...
Most examples that lead to communication and deception indicate our plans to maximize the use of low...
Machine learning plays a vital role in understanding threats, vulnerabilities, and security policies...
A novel Machine Learning (ML) method based on Neural Networks (NN) is proposed to assess radio-frequ...
This study proposes using machine learning to improve Wi-Fi network security. As Wi-Fi networks spre...
The landscape of network analysis is ever-evolving as the fields of technology and business progress...