IBM Bullish on Homomorphic Encryption

Yet more interest in this technique by major players.

IBM bets homomorphic encryption is ready to deliver stronger data security for early adopters

By Chris O'Brien In Venturebeat

The topics of security and data have become almost inseparable as enterprises move more workloads to the cloud. But unlocking new uses for that data, particularly driving richer AI and machine learning, will require next-generation security.

To that end, companies have been developing confidential computing to allow data to remain encrypted while it is being processed. But as a complement to that, a security process known as fully homomorphic encryption is now on the verge of making its way out of the labs and into the hands of early adopters after a long gestation period.

Researchers like homomorphic encryption because it provides a certain type of security that can follow the data throughout its journey across systems. In contrast, confidential computing tends to be more reliant upon special hardware that can be powerful but is also limiting in some respects.

Companies such as Microsoft and Intel have been big proponents of homomorphic encryption. Last December, IBM made a splash when it released its first homomorphic encryption services. That package included educational material, support, and prototyping environments for companies that want to experiment.

In a recent media presentation on the future of cryptography, IBM director of strategy and emerging technology Eric Maass explained why the company is so bullish on “fully homomorphic encryption” (FHE).

“FHE is a unique form of encryption, and it’s going to allow us to compute upon data that’s still in an encrypted state,” Maass said.  ... " 

Data Privacy via Fully HomoMorphic Encryption

In CoinDesk

Using ‘Holy Grail’ of Data Privacy Technology Dec 21, 2020 at 7:51 a.m. EST By Tanzeel Akhtar

FHE is an emerging technology – often described as the "holy grail" of encryption – designed to allow data to stay encrypted when being processed or analyzed in cloud or third-party environments.

IBM said last week its new service, developed in-house, will allow clients to start experimenting with technology to improve the privacy of their internal IT architectures.

“While current encryption techniques allow data to be protected during storage and in transit, data must be decrypted while it is being processed or analyzed – creating a window of opportunity where data is more vulnerable to theft or exposure,” said IBM. 

Data leaks have become a major issue for enterprises. One making headlines this week saw personal details of clients of cryptocurrency hardware wallet maker Ledger exposed on an online forum.

Research and advisory company, Gartner predicts that by 2025 at least 20% of businesses will be budgeting for programs that require homomorphic encryption, up from less than 1% currently. ... "

FHE Encryption Getting Support from DARPA

The approach is getting more support.    Will post quantum decryption threaten it?

Intel will develop a fully homomorphic encryption chip for DARPA  BY MARIA DEUTSCHER

Intel Corp. today announced that it has been entrusted by the U.S. Defense Advanced Research Projects Agency to develop a chip that will enable applications to work with encrypted data without having to unscramble it first.

The chip will use an emerging encryption method known as fully homomorphic encryption to facilitate such processing. The project was announced today and is described as a multiyear program that will also include Microsoft Corp., which will assist with development. 

In the enterprise, it’s standard practice to encrypt data both when it’s sitting in storage and while it’s zipping across the network. Encryption can prevent hackers from reading records if they gain access to them in a breach. But current cryptography methods don’t block all eavesdropping attempts.

The weak point is that encrypted data has to be unscrambled by the applications that use it before they can carry out computations. That creates opportunities for hackers to access sensitive information while it’s kept in a readable form. With the chip it will develop for DARPA, Intel hopes to reduce the risks stemming from the requirement to unscramble data by harnessing fully homomorphic encryption, or FHE for short, which allows applications to process information without decrypting it.  ...'

IBM Makes Encryption Paradox Practical in IEEE Spectrum

More on FHE and IBM.   From IEEE Spectrum ... 

IBM Makes Encryption Paradox Practical  in IEEE Spectrum

“Fully homomorphic” cryptography allows partial access to digital vaults without ever opening their locks    By Dan Garisto

How do you access the contents of a safe without ever opening its lock or otherwise getting inside? This riddle may seem confounding, but its digital equivalent is now so solvable that it’s becoming a business plan. 

IBM is the latest innovator to tackle the well-studied cryptographic technique called fully homomorphic encryption (FHE), which allows for the processing of encrypted files without ever needing to decrypt them first. Earlier this month, in fact, Big Blue introduced an online demo for companies to try out with their own confidential data. IBM’s FHE protocol is inefficient, but it’s workable enough still to give users a chance to take it for a spin. 

Today’s public cloud services, for all their popularity, nevertheless typically present a tacit tradeoff between security and utility. To secure data, it must stay encrypted; to process data, it must first be decrypted. Even something as simple as a search function has required data owners to relinquish security to providers whom they may not trust.

Yet with a workable and reasonably efficient FHE system, even the most heavily encrypted data can still be securely processed. A customer could, for instance, upload their encrypted genetic data to a website, have their genealogy matched and sent back to them—all without the company ever knowing anything about their DNA or family tree. 

At the beginning of 2020, IBM reported the results of a test with a Brazilian bank, which showed that FHE could be used for a task as complex as machine learning. Using transaction data from Banco Bradesco, IBM trained two models—one with FHE and one with unencrypted data—to make predictions such as when customers would need loans.

Even though the data was encrypted, the FHE scheme made predictions with accuracy equal to the unencrypted model. Other companies, such as Microsoft and Google have also invested in the technology and developed open-source toolkits that allow users to try out FHE. These software libraries, however, are difficult to implement for anyone but a cryptographer, a problem IBM hopes to remedy with its new service.           

“This announcement right now is really about making that first level very consumable for the people [who] are maybe not quite as crypto-savvy,” said Michael Osborne, a security researcher at IBM.

One of the problems with bringing FHE to market is that it must be tailor-made for each situation. What works for Banco Bradesco can’t necessarily be transferred seamlessly over to Bank of America, for example.   .... "

Homomorphic Standards, Sample Efforts

Very useful piece with links to alternate standards and company efforts underway.  Much more at the link

Homomorphic Encryption Standardization

An Open Industry / Government / Academic Consortium to Advance Secure Computation

Standards Meetings

Additional introductory material on homomorphic encryption can be found on the Homomorphic Encryption Wikipedia page.

STANDARDIZATION

There are several reasons why we think this is the right time to standardize homomorphic encryption.

There is already dire need for easily available secure computation technology, and this need will be getting stronger as more companies and individuals switch to cloud storage and computing. Homomorphic encryption is already ripe for mainstream use, but the current lack of standardization is making it difficult to start using it.

Specifically, the current implementations are not easy enough to use by non-experts. The standard will push to uniformize and simplify their API, and educate the application developers about to use them.

The security properties of RLWE-based homomorphic encryption schemes can be hard to understand. The standard will present the security properties of the standardized scheme(s) in a clear and understandable form.

BASICS OF HOMOMORPHIC ENCRYPTION

Fully homomorphic encryption, or simply homomorphic encryption, refers to a class of encryption methods envisioned by Rivest, Adleman, and Dertouzos already in 1978, and first constructed by Craig Gentry in 2009. Homomorphic encryption differs from typical encryption methods in that it allows computation to be performed directly on encrypted data without requiring access to a secret key. The result of such a computation remains in encrypted form, and can at a later point be revealed by the owner of the secret key.... "

FHE for Using Encrypted Data

Very nicely done piece on the seeming paradox of FHE:

IBM Makes Encryption Paradox Practical  in IEEE Spectrum.

“Fully homomorphic” cryptography allows partial access to digital vaults without ever opening their locks  By Dan Garisto

How do you access the contents of a safe without ever opening its lock or otherwise getting inside? This riddle may seem confounding, but its digital equivalent is now so solvable that it’s becoming a business plan. 

IBM is the latest innovator to tackle the well-studied cryptographic technique called fully homomorphic encryption (FHE), which allows for the processing of encrypted files without ever needing to decrypt them first. Earlier this month, in fact, Big Blue introduced an online demo for companies to try out with their own confidential data. IBM’s FHE protocol is inefficient, but it’s workable enough still to give users a chance to take it for a spin. 

Today’s public cloud services, for all their popularity, nevertheless typically present a tacit tradeoff between security and utility. To secure data, it must stay encrypted; to process data, it must first be decrypted. Even something as simple as a search function has required data owners to relinquish security to providers whom they may not trust. .... "

See IBM's   Homomorphic Encryption Services demonstration  "  Unlock the value of sensitive data without decryption to preserve privacy .. " 

Researchers Propose Compiler for Homomorphic Encryption

 Still with some technical barriers.  See below for some details.  Links to more.

Researchers propose Porcupine, a compiler for homomorphic encryption

Kyle Wiggers  @Kyle_L_Wiggers  January 22, 2021 

Homomorphic encryption (HE) is a privacy-preserving technology that enables computational workloads to be performed directly on encrypted data. HE enables secure remote computation, as cloud service providers can compute on data without viewing highly sensitive content. But despite its appeal, performance and programmability challenges remain a barrier to HE’s widespread adoption.

Realizing the potential of HE will likely require developing a compiler that can translate a plaintext, unencrypted codebase into encrypted code on the fly. In a step toward this, researchers at Facebook, New York University, and Stanford created Porcupine, a “synthesizing compiler” for HE. They say it results in speedups of up to 51% compared to heuristic-driven, entirely hand-optimized code.  ... "

Homomorphic Encryption Environment

More on what IBM is doing in the space of 'Fully Homomorphic Encryption', which is now including 'quantum safe' capabilities.   Here is a definition of that capability from the WP.

Now IBM is putting out an experimental capability for testing.

IBM launches experimental homomorphic data encryption environment for the enterprise

Is it possible for fully homomorphic encryption to be a “game-changer” for data privacy? IBM intends to find out.

IBM has launched a fully homomorphic encryption (FHE) test service for the enterprise in the first step to bringing in-transit encrypted data analysis into the commercial sector. 

IBM said on Thursday that the new FHE solution, IBM Security Homomorphic Encryption Services, will allow clients to start experimenting with how the technology could be implemented to enhance the privacy of their existing IT architecture, products, and data. 

FHE, considered by some as the "Holy Grail" of encryption, as it is a form of encryption that allows data to remain encrypted when being processed. 

The concept behind FHE is to plug the gap between securely-encrypted data held in storage and the need to decrypt while this information is in use -- a requirement in data processing or analysis -- which can create protection issues.  ... " 

Fully Homomorphic Encryption

Despite my previous experience in crypto, new to me: Homomorphic Encryption.

IBM completes successful field trials on Fully Homomorphic Encryption
FHE allows computation of still-encrypted data, without sharing the secrets.

Jim Salter, Arstechnica

We're already accustomed to data being encrypted while at rest or in flight—FHE offers the possibility of doing computations on it as well, without ever actually decrypting it.

Yesterday, Ars spoke with IBM Senior Research Scientist Flavio Bergamaschi about the company's recent successful field trials of Fully Homomorphic Encryption. We suspect many of you will have the same questions that we did—beginning with "what is Fully Homomorphic Encryption?"

FHE is a type of encryption that allows direct mathematical operations on the encrypted data. Upon decryption, the results will be correct. For example, you might encrypt 2, 3, and 7 and send the three encrypted values to a third party. If you then ask the third party to add the first and second values, then multiply the result by the third value and return the result to you, you can then decrypt that result—and get 35.

You don't ever have to share a key with the third party doing the computation; the data remains encrypted with a key the third party never received. So, while the third party performed the operations you asked it to, it never knew the values of either the inputs or the output. You can also ask the third party to perform mathematical or logical operations of the encrypted data with non-encrypted data—for example, in pseudocode, FHE_decrypt(FHE_encrypt(2) * 5) equals 10.   .... "