Titolo della tesi: Cybersecurity at the Intersection of Modern and Future Networking
The Internet, one of the most important inventions of the past century, has transformed our everyday life. “We are all now connected by the Internet, like neurons in a giant brain” quoted Stephen Hawking, which exactly mirrors today’s Internet dimensions. With its exponential growth, also numerous novel malicious activities started threatening the security of end users, infrastructures, and systems. Therefore, cybersecurity – and specifically network security – emerged as a discipline for combating these threats against networked systems and infrastructures.
In the past years, novel networking paradigms have changed the networking perspective. In particular, Software Defined Networking (SDN) – especially network programmability – comprises the next-generation networking paradigms aiming to provide high-performance networked services, which the operators can flexibly manage and program. Considered more as a revolutionary approach, Information-Centric Networking (ICN) proposes a radical change in the Internet core, especially concerning the communication model. While bringing innovation for making the Internet a better place, these networking prototypes offer means to run security and privacy measures at the network level.
The dissertation focuses on cybersecurity aspects at the intersection of modern networking, focusing on programmable networks, and future networking, mainly concerning the ICN. Additionally, the dissertation addresses the use of Machine Learning (ML) for network security in a two-fold direction: (i) leveraging ML as a tool for providing better network security solutions, and (ii) elaborating on the complexity and lack of transparency that ML-based mechanisms expose the network to. Specifically, the dissertation addresses open challenges in programmable networks, including detecting timeless threats by leveraging ML capabilities. Additionally, it contributes to new security threats deriving from novel functionalities that ICN proposes. Lastly, this dissertation explores the security and privacy aspects of the coexistence between the current networking paradigm with the future ICN paradigm.
Keywords: Cybersecurity · Information-Centric Networking · Programmable Networks · Machine Learning · Next-Generation Networks