SDN network's policies are updated dynamically at a high pace. As a result, conflicts between policies are prone to occur. Due to the large number of switches and heterogeneous policies within a typical SDN network, detecting ...

An adaptive task difficulty assignment method which we reckon as balanced difficulty task finder (BDTF) is proposed in this paper. The aim is to recommend tasks to a learner using a trade-off between skills of the learner ...

With the increasing threats of security attacks, Machine learning (ML) has become a popular technique to detect those attacks. However, most of the ML approaches are black-box methods and their inner-workings are difficult ...

Machine-learning based Intrusion Detection and Prevention Systems provide significant value to organizations because they can efficiently detect previously unseen variations of known threats, new threats related to known ...

Dynamical systems are capable of performing computation in a reservoir computing paradigm. This paper presents a general representation of these systems as an artificial neural network (ANN). Initially, we implement the ...

Although deep learning has recently increased in popularity, it suffers from various problems including high computational complexity, energy greedy computation, and lack of scalability, to mention a few. In this paper, ...