We study automated intrusion response and formulate the interaction between an attacker
and a defender as an optimal stopping game where attack and defense strategies evolve …

We study automated intrusion prevention using reinforcement learning. Following a novel
approach, we formulate the interaction between an attacker and a defender as an optimal …

We study automated intrusion response for an IT infrastructure and formulate the interaction
between an attacker and a defender as a partially observed stochastic game. To solve the …

Detection of abnormal internet traffic has become a significant area of research in network
security. Due to its importance, many predictive models are designed by utilizing machine …

This paper presents the estimation methods of packet inter-arrival times. The approach is
based on neural network models for predicting the packet inter-arrival times by learning …

Network traffic has been studied extensively since new findings by Taqqu et. al.(1994),
which has shown that network traffic is not memoryless. Such traffic has been called self …

Long range dependence (LRD) in network traffic is known for sometime. Numerous efforts
have been made to model and analyze effect of such traffic on user experience, resource …

In this work, we aim to evaluate how good are the information criteria AIC and BIC inferring
which is the best stochastic process to describe Ethernet inter-packet times. Also, we check if …

ncreasing access to the Internet is producing profound influence around the World. More
and more people are taking advantage of the Internet to obtain information, communicate …