Sunscreen
@SunscreenTech
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Add Fully Homomorphic Encryption (FHE) to your app in minutes, not months.
encrypted
Joined April 2021
🌞 Introducing SPF🧴🔒 Our Secure Processing Framework (SPF) enables developers to bring FHE to any web2 or web3 app in a performant and scalable way. ✅ One program, any chain ✅ State-of-the-art performance ✅ Future-proof with post-quantum security
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Spot on. AI needs private inference YESTERDAY.
Take ChatGPT for example. Everything you type: - can be used as evidence against you in court (there’s no legal confidentiality like you’d have with a therapist or lawyer): https://t.co/WteQqhFeLk - can be used by default to train the model: https://t.co/otujGmtvUw That’s
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Full Self-Driving Supervised improves US road safety by over 80%, saving lives & preventing injuries
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Both TEEs and FHE enable privacy-preserving computation, but they approach the problem from different angles. If performance is critical and trust in hardware is acceptable → TEE is a practical choice. If absolute data privacy and decentralization matter most → FHE is the
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FHE lets you compute directly on encrypted data, without needing to decrypt data at all. Benefits: 1/ Trust in math; cryptographic guarantees 2/ Good for cloud or decentralized systems where zero trust is important 3/ When data is never decrypted, the attack surface is reduced
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TEEs run code inside a secure enclave. Benefits: 1/ near-native speed 2/ great for fast, local, centralized execution Disadvantages: 1/ Have to trust hardware and vendor 2/ Be ok with side channel attack risk
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Private compute isn't just one thing, it's a spectrum of a trust model. TEEs trust hardware, FHE trusts math. Regardless of whether you're building an AI or blockchain app, you should ask: what (or who) are you trusting and whether that trust assumption works for your app.
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ZK goes far with crypto. ZK goes even further with FHE and crypto.
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Sleigh the season with the most personal gift around. Get them a Cameo video!
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Introducing Circuit Bootstrapping (CBS) - cmux A purpose-built, and novel encrypted computing environment, based on Circuit Bootstrapping, that significantly reduces latency and increases parallelism in FHE operations.
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My ultimate vision for FHE is that all software must run on encrypted data by default, shifting the internet from trust-based to trustless. I believe this will unlock a new paradigm of human computer interaction where our true preferences, behaviors, and interactions can shape
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Builders shouldn't have to rebuild their application or learn a new programming language to integrate privacy. Ship private apps with FHE while keeping your stack, and without changing a thing.
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Read our paper on Parasol and CBS-cmux below. Accepted to IEEE S&P 2026 (Oakland). https://t.co/8hJfmfwYAq
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Excited to share that Parasol, our FHE compiler encompassing a virtual processor with a custom ISA and a low-level library for FHE ops already supports circuit construction using CBS-cmux. Learn more here:
Fully Homomorphic Encryption (FHE) is the holy grail of cryptography, allowing devs to compute on encrypted data. However, writing FHE programs is a nightmare. That's why we've built a compiler that makes it incredibly simple. Write in C. Tag the parts you want to encrypt.
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Bootstrapping is the main bottleneck in modern FHE schemes. We show that our CBS-based approach with multiplexers delivers more efficient FHE circuits over Programmable Bootstrapping (PBS) by increasing intra-circuit parallelism and data re-use. Eg: 16-bit comparison 👇
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Introducing Circuit Bootstrapping (CBS) - cmux A purpose-built, and novel encrypted computing environment, based on Circuit Bootstrapping, that significantly reduces latency and increases parallelism in FHE operations.
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Good post done in good faith by @EliBenSasson so let's break it down point by point and debunk some of his concerns: 1/ "FHE solves confidentiality, but not integrity. In this sense it's complimentary to ZK, and in an ideal world you'd want to use the two of them combined."
Privacy matters -- Difference between TEE, ZK, MPC and FHE - Last one! Today we explain: FHE FHE - Fully Homomorphic Encryption is a very powerful cryptographic privacy paradigm. It solves confidentiality, but not integrity. In this sense it's complimentary to ZK, and in an
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@EliBenSasson have you seen the SPF (Secure Processing Framework? made by @SunscreenTech ? They enable developers to create FHE programs in C with extremely few changes. The programs are available in web2 and any blockchain as long as there is a compatible oracle and the necessary smart
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@EliBenSasson with regards to problems with FHE 1. there's some really good work by @SunscreenTech here with Parasol compiler which enables you to write custom programs directly in C 2. We still need efficient proving for FHE circuits but meanwhile we can work with running FHE programs
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most people don't care about privacy, unless it enables a new technology or use case.
Say something true, in an interesting way.
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Trump says NEWSMAX is 'terrific!' Click below to find out why...
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