Computational Intelligence for Security in Named Data Networking

Named Data Networking (NDN) has recently been considered as a promising paradigm for the next-generation Internet. One of the main design requirements for the NDN architectures -since the beginning of their design- has been strong security. To make NDN a fully working system at Internet scale, there are still many missing pieces to be filled in. In this book, we study the most important security problems in NDN in order to defense against new forms of attacks, ensure privacy, achieve high availability, and block malicious network traffics belonging to attackers or at least limit their effectiveness. In order to protect NDN infrastructure, we need flexible, adaptable and robust defense systems which can make intelligent and real-time decisions to enable network entities to behave in an adaptive and intelligent manner. In this context, the characteristics of Computational Intelligence (CI) methods make them suitable to be applied to the problem of NDN security, which can highlight promising new research directions. Hence, we suggest new hybrid CI-based methods to make NDN a more reliable and viable architecture for the future Internet.

Autorentext

Amin Karami completed his PhD at the Universitat Politècnica de Catalunya Barcelona Tech (UPC), Spain in Feb. 2015. His current research interests include computational intelligence and learning approaches and methodologies, big data analytics, named data networking, network security and uncertainty visualization.