фото показано с : zycrypto.com

The terms ‘sensitive data’ and ‘encryption’ go together like warm apple pie and ice cream. Yet, debates rage about which encryption provides the strongest security protection for sensitive information.

Although end-to-end encryption (E2EE) is the best-known form – doubtless a consequence of its use in messaging platforms like WhatsApp – some technologists believe Fully Homomorphic Encryption (FHE) is the real heavyweight champ.

While the name itself might be a mouthful, the appeal of FHE is rather easy to explain: it enables computation on encrypted data without the need to decrypt it.

Although end-to-end encryption provides reassurance to millions of users that their data is safe from prying eyes, it traditionally comes with a significant limitation: the data must be decrypted and re-encrypted before reaching its destination.

FHE, in contrast, permits direct computation on encrypted data. This effectively means that sensitive medical or financial data can be analyzed without exposing the underlying information—even in untrusted environments like public clouds.

While many technologists fear the growing power of quantum computing, which threatens to break many current encryption methods, FHE’s mathematical foundations are said to make it impervious to quantum attacks – future-proofing data privacy in an increasingly uncertain technological age.

Major tech companies are judged on the quality of their cybersecurity defenses. So, it’s no surprise that FHE continues to be the subject of intense exploration. Search giant Google, for instance, has its own HEIR compiler toolchain, which aims to make FHE applications run efficiently across different hardware platforms. IBM, Microsoft, Oracle, and Alibaba – the latter of which holds the most FHE patents – are also investing heavily in the technology.

From healthcare and finance to electronic voting and cloud computing, FHE has immense potential to protect user data and repel brute-force attacks from cyber miscreants. Something that will be extremely important when billions of data points are exchanging information in the smart cities of the near future.

In the blockchain space, projects are tapping into FHE to provide users with ‘on-chain confidentiality.’ Layer-2 blockchain Fhenix is one such project.

This FHE-based L2 uses Fully Homomorphic Encryption to address Ethereum’s lack of native encryption. It even boasts its own iteration of the latter’s EVM: the fhEVM. With this, Solidity developers can deploy encrypted smart contracts and build privacy-preserving decentralized applications (dApps) without extensive cryptographic expertise.

To date, Fhenix has raised $22 million from a slew of high-profile Web3 VCs and angel investors, reflecting the broad appeal of FHE in a crypto context. Of course, there is an element of preaching to the converted here: perhaps no sector appreciates privacy quite as much as DeFi, which is why Fhenix has made such a big impact early in its roadmap.

Of the many proposed use cases for Fhenix technology, private on-chain auctions, and social networks have been cited. In truth, the platform’s ability to ensure transaction inputs and states remain encrypted throughout the computation process makes it suitable for building a slew of privacy-focused applications.

Ultimately, FHE’s promise lies not just in its technical capabilities but also in its potential to change how we think about data privacy and security fundamentally. In a world where data breaches can leave reputations in tatters and bank accounts in arrears, FHE offers a path to secure computation while truly maintaining the utility of sensitive information.

While end-to-end encryption has its place, Fully Homomorphic Encryption is the best option currently available. We would do well to make the most of it.

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