Deep Residual Networks have recently been shown to significantly improve the
performance of neural networks trained on ImageNet, with results beating all previous …

In network traffic classification, it is important to understand the correlation between network
traffic and its causal application, protocol, or service group, for example, in facilitating lawful …

The COVID-19 pandemic led to the adoption of severe measures to counteract the spread of
the infection. Social distancing and lockdown measures modified people's habits, while the …

Traffic analysis is a compound of strategies intended to find relationships, patterns,
anomalies, and misconfigurations, among others things, in Internet traffic. In particular, traffic …

This survey paper describes the significant literature survey of Sustainable Smart Cities
(SSC), Machine Learning (ML), Data Mining (DM), datasets, feature extraction and selection …

Flow monitoring has become a prevalent method for monitoring traffic in high-speed
networks. By focusing on the analysis of flows, rather than individual packets, it is often said …

Traffic classification groups similar or related traffic data, which is one main stream
technique of data fusion in the field of network management and security. With the rapid …

Personal cloud storage services are gaining popularity. With a rush of providers to enter the
market and an increasing offer of cheap storage space, it is to be expected that cloud …

Increased user concern over security and privacy on the Internet has led to widespread
adoption of HTTPS, the secure version of HTTP. HTTPS authenticates the communicating …

This work addresses the performance evaluation of Content Centric Networks (CCN).
Focusing on a realistic YouTube-like catalog, we conduct a very thorough simulation study …