Giacomo Zonneveld

Giacomo Zonneveld, Giulia Rafaiani, Marco Baldi

Certification of digital documents, such as academic credentials, seems a particularly suitable application for the use of blockchain and distributed ledger technologies. Indeed, these technologies enable decentralized certification systems that rely on the immutability and persistence of their distributed ledgers. However, in the absence of a central trusted authority, it is not easy to guarantee the authenticity of the connection between the real identity of an academic institution and the digital identity of the certificate issuer. In this paper, we demonstrate that one of such systems, known as Block.co, has a vulnerability that allows the production of forged certificates that are recognized as valid by the system. Since this is an inherent limitation of the approach used for blockchain-based certification, our attack is likely to be extendable to other systems adopting the same approach.

Giacomo Zonneveld, Lorenzo Principi, Marco Baldi

Early detection of network intrusions and cyber threats is one of the main pillars of cybersecurity. One of the most effective approaches for this purpose is to analyze network traffic with the help of artificial intelligence algorithms, with the aim of detecting the possible presence of an attacker by distinguishing it from a legitimate user. This is commonly done by collecting the traffic exchanged between terminals in a network and analyzing it on a per-packet or per-connection basis. In this paper, we propose instead to perform pre-processing of network traffic under analysis with the aim of extracting some new metrics on which we can perform more efficient detection and overcome some limitations of classical approaches. These new metrics are based on graph theory, and consider the network as a whole, rather than focusing on individual packets or connections. Our approach is validated through experiments performed on publicly available data sets, from which it results that it can not only overcome some of the limitations of classical approaches, but also achieve a better detection capability of cyber threats.