Stanford cryptography researchers are building Espresso, a privacy-focused blockchain

If blockchain technology is to reach true mass adoption, it will have to become cheaper and more efficient. Low transaction throughput on some of the most popular blockchains, most notably Ethereum, has kept gas fees high and hindered scalability. A host of new projects has cropped up to improve efficiency in the blockchain space, each with its own set of tradeoffs, including proof-of-capacity blockchain Subspace, which announced a $32.9 million funding round last week.

Now, a team of researchers from Stanford University’s applied cryptography research group has entered the fray. The team is coming out of stealth mode with Espresso, a new layer-one blockchain they are building to allow for higher throughput and lower gas fees while prioritizing user privacy and decentralization. Espresso aims to optimize for both privacy and scalability by leveraging zero-knowledge proofs, a cryptographic tool that allows a party to prove a statement is true without revealing the evidence behind that statement, CEO Ben Fisch told TechCrunch in an interview.

Espresso Systems, the company behind the blockchain project, is led by Fisch, chief operating officer Charles Lu and chief scientist Benedikt Bünz, collaborators at Stanford who have each worked on other high-profile web3 projects, including the anonymity-focused Monero blockchain and BitTorrent co-founder Bram Cohen’s Chia. They’ve teamed up with chief strategy officer Jill Gunter, a former crypto investor at Slow Ventures who is the fourth Espresso Systems co-founder, to take their blockchain and associated products to market.

Read more

Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.