When monitoring interactions within a social network, meetings or contacts between different
members of the network are recorded. This paper addresses the problem of using the …

Network security represents a keystone to ISPs, who need to cope with an increasing
number of network attacks that put the network's integrity at risk. The high-dimensionality of …

Many types of automated visual surveillance systems have been presented in the recent
literature. Most of the schemes require custom equipment, or involve significant complexity …

Fuzzy C-means (FCM) clustering has been used to distinguish communication network
traffic outliers based on the uncommon statistical characteristics of network traffic data. The …

With the rapid development of information technology and internet, all kinds of industry data
exploded causing difficult to analyze and mine useful information from big data. Traditional …

While the growth of cloud-based technologies has benefited the society tremendously, it has
also increased the surface area for cyber attacks. Given that cloud services are prevalent …

While traditional network security methods have been proven useful until now, the flexibility
of machine learning techniques makes them a solid candidate in the current scene of our …

The recent development of physics informed neural networks (PINNs) has explored the
inclusion of prior physics knowledge into the objective function of deep learning models as …

Anomalies are integral part of every system's behavior and sometimes cannot be avoided.
Therefore it is very important to timely detect such anomalies in real-world running power …

In the post-pandemic world, surveillance cameras play a key aspect when it comes to
detecting various kinds of security risks. These can range from burglars entering a premises …