Marco Zecchini

Ricercatore

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stanza:

A101

telefono:

+39 0677274087

Biography

I am an Assistant Professor at the Università di Roma “La Sapienza” working at the intersection of cryptography and its application in web applications and blockchain. My research focuses on applying cryptographic tools to real-world use cases such as fighiting misinformation, fair exchange without trusted parties, light clients for blockchain and secure machine learning. I hold a PhD in Data Science from Sapienza University of Rome.

My profile lies at the intersection between the world of theoretical cryptography and real-world cryptography: in fact, I am able to analyze in detail theoretical results from papers in prestigious conferences/journal while at the same time recognizing the limitations of these techniques in real-world applications. This makes me an original and rare profile in the cybersecurity research landscape, because I combine the theoretical frontier with solutions that truly work in real systems.

I coauthored around 20 papers and some of them have been published in international journals or prestigious cybersecurity conferences (S\&P, IACR Real World Crypto, NDSS).

I held lectures in various academic programs and international schools, including the Algorand International Summer School (2022), and I currently lecture the course “Principles of Computer Science II” at Sapienza University of Rome.

My writing, teaching, and communication style follow a simple principle: I always try to communicate as I would do with my beloved grandma, leaving nothing unsaid or taken for granted!

Research interest

During my PhD, I focused on the design of new blockchain architectures and protocols aimed at reducing the trust assumptions underlying identity management and asset certification.

My research investigated how to combine decentralized consensus and selective trust, proposing practical systems that leverage blockchain transparency while preserving user control over identity attributes. The results were applied in various contexts, from public administration to copyright management systems.

In my recent research path, I have explored how cryptographic proofs can enhance verifiability in decentralized systems. A main direction concerns proving the authenticity of image transformations: I designed and implemented a proof system that allows users to demonstrate, without revealing the original image, that a given transformation (e.g., filtering, cropping) has been correctly applied. This research was presented at the Berkeley Security Seminar and appears at the IEEE Symposium on Security and Privacy 2025. The goal is to promote trustworthy sharing of digital media in adversarial and misinformation-prone environments.

I have also worked to improve the scalability and decentralization of blockchain infrastructure. I recently co-authored a protocol for superlight clients that uses succinct cryptographic proofs to verify the correctness of blockchain state queries with minimal communication and computation. This makes it possible for resource-constrained devices—such as smartphones or embedded systems—to interact securely with blockchains, enabling a wider class of applications and users.

Finally, I have recently work on a cryptographic protocol that allows a user to obtain standard cryptographic signatures from a notary (acting as a TLS Oracle as Deco or TLSNotary) on data downloaded via TLS from a server, without the notary seeing the data. The user will only prove that the data comes from a TLS server and that it complies with certain policies, following a predicate blind signature protocol (first proposed in an IACR Crypto 2024 paper). This research will appear at the Network and Distributed System Security (NDSS) Symposium 2026. In the near future, I will focus on using cryptography to enhance security and privacy in machine learning applications (secure inference, secure training).

In general, by combining theoretical insights from cryptography with practical system design, I aim to build tools that are secure, efficient, and usable in real-world scenarios.

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