Homomorphic encryption is a type of cryptography that allows for computations to be performed on encrypted data. This allows sensitive information, such as financial or health records, to be securely processed without the need for decryption. In addition, homomorphic encryption can prevent unauthorized users from accessing protected data even if they are able to obtain access to the underlying encryption keys.
Origins 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. Source: homomorphicencryption.org
Why is homomorphic encryption important?
Homomorphic encryption is important because it allows for sensitive information to be processed without the need for decryption. This means that homomorphic encryption can prevent unauthorized users from accessing protected data even if they are able to obtain access to the underlying encryption keys. In addition, homomorphic encryption can be used to securely process financial or health records without the need for decryption.
What are the challenges of homomorphic encryption?
While homomorphic encryption has many potential benefits, it also faces a number of challenges. One challenge is that homomorphic encryption typically requires complex and time-consuming computations, which can limit its practical applications in real-world scenarios. Another issue is that homomorphic encryption makes it difficult to verify the accuracy of data or results, as it may be impossible to check them without access to the decryption keys. Finally, homomorphic encryption can potentially make it more difficult to detect and prevent cyberattacks, as attackers may be able to use homomorphic encryption techniques in order to mask their activities.
Despite these challenges, homomorphic encryption remains a promising technology that is likely to play an increasingly important role in the future of cybersecurity and data protection. If you are interested in learning more about homomorphic encryption or getting started with this emerging technology, there are many resources available online, including tutorials and open source tools. To get started, simply do a quick search for homomorphic encryption or download one of the popular software packages like FHE-Py and GaMES. With the right tools and knowledge, you can start taking advantage of homomorphic encryption today
Types of Homomorphic Encryption
Homomorphic Encryption or HE, as it’s popularly known – comes in multiple types. And all of those types function slightly differently. However, the basic method of their function is the same: they use an arithmetic circuit for performing computations instead of a boolean course, which is used in other computing methods.
1. Partially Homomorphic Encryption
This type of Homomorphic Encryption allows certain mathematical functions (i.e., addition, multiplication, etc.) to be performed without decrypting the data, while for other functions, you need to decrypt it.
2. Somewhat Homomorphic Encryption
This type of encryption allows certain mathematical functions to be performed unlimited times on the encrypted data. In contrast, other functions can be performed only a fixed number of times, or up to a certain level of complexity.
3. Fully Homomorphic Encryption
As its name suggests, this type of encryption allows all functions to be performed unlimited times and up to any level of complexity without requiring the decryption of data. It is the most secure type of Homomorphic Encryption that you can get today.
With this in mind, now let’s take a little more detailed look at Fully Homomorphic Encryption (FHE). Source: ssl2buy.com
There are several reasons why 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. Implementations of leading schemes (CKKS, BFV, BGV, etc…) have begun to be adopted to address the needs of privacy-protected computations. 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. Source: homomorphicencryption.org
Examples of Homomorphic Encryption
Supply Chain Security
Most companies have trusted third parties that they rely upon as part of their business. These contractors, vendors, etc. often need access to the company’s sensitive and proprietary data in order to do their jobs. Recent events have demonstrated the risks of insecure supply chains and how cybercriminals will target the weakest link in the chain to achieve their objectives. This means that entrusting sensitive data to a partner may leave an organization open to an expensive and damaging data breach. Homomorphic encryption can help a company to protect itself against these supply chain risks. If all data provided to trusted third parties for processing is encrypted, then a breach of that data poses no risk to the company. This allows an organization to outsource critical data processing with minimal risk. Source: keyfactor.com
In recent years, the data protection regulatory landscape has grown increasingly complex. New regulations like the EU’s Data Protection Regulation (GDPR) have provided data subjects with new rights and placed additional responsibilities and restrictions on businesses. One GDPR rule that many businesses are struggling with is the requirement that the data of EU citizens remains within the EU or in countries or companies with equivalent data security standards. The Schrems II decision in 2020 invalidated one of the main ways in which EU-US data flows were justified under GDPR, which caused problems for many US companies with EU citizens. Laws like the GDPR clearly state that their requirements do not apply to encrypted data. With homomorphic encryption, a company could potentially store and process data on systems outside the EU and then only decrypt it on servers in locations that comply with GDPR requirements. Source: keyfactor.com
Private Data Analytics
Data analytics is how many companies make their money. Businesses like Facebook are able to provide “free” services by collecting information about their users, processing it, and selling this information to third parties for targeted advertising. However, this monetization of personal data is controversial. Many people are unhappy with companies building in-depth profiles about them without any visibility and control over the data collected and how it is used. Homomorphic encryption provides a potential solution to this problem. With homomorphic encryption, a company like Facebook could perform the data analytics that it needs without the ability to view or access the original data. If encryption keys are controlled by users, this provides the potential for private, targeted advertising.mSource: keyfactor.com
Homomorphic encryption is a powerful tool that can be used to protect data and enable new privacy-preserving applications. However, homomorphic encryption is still in its early stages of development and standardization. This means that there are few homomorphic encryption schemes that have been well-vetted and there is no clear “best” scheme. As homomorphic encryption schemes become more mature, we expect to see more widespread adoption and use cases for this technology. In the meantime, businesses should work closely with trusted partners to ensure that each party has access only to the information that they need and is safeguarded against supply chain threats. They should also carefully consider their regulatory compliance requirements when deciding whether homomorphic encryption could be a useful tool for them. Additionally, homomorphic encryption may present an opportunity for private data analytics, where user-controlled data encryption keys provide unprecedented control over personal data. Overall, homomorphic encryption is an exciting technology that holds great promise for the future of data security and privacy.