This paper aims at the requirement for an interactive learning framework which empowers
the successful checking of disorder in a patient. Principal component analysis stands out as …

Botnets have carved a niche in contemporary networking and cybersecurity due to the
impact of their operations. The botnet threat continues to evolve and adapt to …

Analyzing non-labeled data is a major concern in the field of intrusion detection as the attack
clusters are continuously evolving which are unknown for the system. Many studies have …

Hybrid Anomaly Detection Model (HADM) is a platform that filters network traffic and
identifies malicious activities on the network. The platform applies data mining techniques to …

Context Machine learning-based security detection models have become prevalent in
modern malware and intrusion detection systems. However, previous studies show that such …

In a cloud computing environment, future networks will most probably utilize network
functions virtualization (NFV) which is a network architecture concept that proposes …

The ALICE (A Large Ion Collider Experiment) detector at the European Organization for
Nuclear Research (CERN) generates a substantial volume of experimental data, demanding …

Cloud computing offers benefits of sharing computing and network resources among
multiple mobile network operators. To utilize such benefits, in earlier paper we proposed a …

The successful security management of ICT systems and services is essential for an
effective cyber security posture. The main objective is to minimize and control the damage …

New genres of malware are evading detection by using polymorphism, obfuscation and
encryption techniques. Hence, new strategies are needed to overcome the limitations of …