Network Analysis of co-authorship system of University of Sindh authors on Science Direct

Many complex systems have been modelled and analyzed as complex networks. These systems are huge and complex in terms of number of interconnecting components. In this research, we have analyzed the co-authorship network of Sindh university authors on science direct to understand the connectivity pattern of authors who published their articles over time. This research has found that the connectivity pattern of the authors is highly heterogonous due to the emergence of hubs in this system. Further, this network has shown highly clustered behavior with small world effect. These findings based on network analysis suggests that the co-authorship system is depending on few authors frequently publishing multiple papers in this network

Invite Internet Users to Honeynet Security to Improve VoIP Streaming Services

There are group of challenges in VoIP security, VoIP Quality and lots of peoples worked on it e.g., “IPSec security on VoIP”, “VoIP Honeypot architecture”, “cryptography techniques are used to safely transmit the information stream over the network” and many more. Security is a terminology which cannot be a perfect or 100%. For the time being we can be minimizing and protect to the threats but as the technology increases the new threats are also generating day by day. Researchers have applied different patterns, techniques and scenarios to prevent some specific threats and security frameworks for securing VoIP communication. But in this research, we want to analyze the quality of service after applying Honeynet security framework

Network Analysis of 500 Flights of USA Air Transportation System

People's interest in network analysis has grown considerably in last decade. The air transportation network is considered to be a complex network, full of vitality and ramification. The main purpose of this research is to model and analyze, from a network perspective, the US air transportation network, which is one of the unique in its nature in the world. We find several features of complex network of air transportation including local and global such as degree distribution, weighted degree, clustering coefficient and betweenness and closeness centralities. The USA air transportation network has shown small-world behavior and due to non-homogenous distribution of applied network analysis metrics the network is inclined to power-law distribution