Deep packet inspection (DPI) is an established methodology used by ISPs for performance enhancements, security protections, behavioral advertising, and content filtering. However, the limitations of DPI and its applications are becoming more and more evident with the increase in network traffic and the variations in usage patterns. In this exploratory project, the PI will introduce the notion of Deep ``Network" Inspection (DNI) that will go beyond DPI in exploring correlations among multiple networks and other aggregated parameters from multi-genre networks and behaviors. DNI will use broader knowledge including social network relevancies, information network, modalities of accesses, device characteristics, past and present user profiles at various levels of aggregations; thus going far beyond the realm of isolated characterizations of communication networks. Primary goals of DNI include the reduction in the ?search space? for real-time analysis and the complexity of pattern discoveries, and the discovery of relationships which may not be detectable by single-network inspection (such as DPI). The goal of this project is to do an initial study to motivate and explore the capabilities of DNI, the challenges therein, scope of inspections, and potential applications. The outcome of this exploratory study would potentially open up an enriched area for further research in the domains of network science. In terms of broader impact, the proposed project will also instigate researchers in both academics as well as industry to explore this new domain on network inspection, which may have significant potential in a variety of applications, and education of students.
