What Is Fully Homomorphic Encryption?

In this article, we will be studying the topic “What Is Fully Homomorphic Encryption?”. Also, we will look at the topic’s relationship with encryption, data, computations, data privacy, etc.

Meaning Of Fully Homomorphic Encryption

One can say, fully homomorphic encryption is an aspect of encryption scheme where one can randomly reckon a data. Meanwhile, this data is under concealment. However, the purpose of this is to ensure the reckoning on ciphertexts without revealing it throughout the process.  

With this, it increases efficiency in cloud computing and analytics of data. However, there shouldn’t be exposure of confidential informations to an intermediary. On the other hand, some people think it isn’t achievable to carry out computation without converting it to plain form.

The challenge one may face especially is the separation of encryption and decryption keys. This usually happens in traditional encryption schemes. However, one must reveal and encrypted data, before working on it.

The beauty of fully homomorphic encryption (FHE) is that, you mustn’t decrypt a concealed data, before randomly reckoning it. More so, it possess an encryption key. However, all these are in opposition to the traditional schemes.

Importance Of Homomorphic Encryption

The paramount use of this property, is the concealing feature. An entity can reckon a data and will not know the content of it.

Let us give an instance with a hospital setting. An embodiment of medical reports are under homomorphic encryption. With the help of an encryption key, the doctor can obtain patients’ information. He can do this without getting in touch with the actual data in the database.

Differences Between FHE And Its Other Forms.

As regards to the computation of concealed data, homomorphic encryption has various forms. They are partially, somewhat, leveled fully, and fully homomorphic encryption.

Now, we will look at them individually. Partially homomorphic and somewhat homomorphic permits only a unique computation. Also, it limits any sort of reoccurrence. Meanwhile, fully homomorphic encryption permits reoccurrence of computations. It permits numerous computations.

Advantages Of Fully Homomorphic Encryption

  • Storing of very important data on intermediary servers. However, one can still work on the private data while maintaining its encryption. In a situation where the FHE is under security, the server administrators won’t know about the computation.
  • With the use of FHE, there is no compromise existing between data usability and data privacy. On the other hand, there is no importance of eliminating any data privacy attribute while preserving it. 
  • Evidently, FHE faces a lot of attacks. But, it shields off these quantum attacks.

Side Note On Fully Homomorphic Encryption

The optimum priority of heads of companies is to safeguard data effectively. FHE is gearing positively to achieve this.

What Is Meaning of Fully Homomorphic Encryption?

The concept of fully homomorphic encryption has to do with computing data without decrypting it. With FHE, one can send a data under encryption without having the decryption key

What Is Working Method Of Fully Homomorphic Encryption ?

Certainly, for a FHE to encrypt a data, it needs a public key. But, the private key gives the bearer, access to see the data when it is not concealed. FHE is unique in computing data without revealing it. In addition, FHE applies the algebraic system. Also, the use of integers, are set to represent informations. Meanwhile, the use of arithmetic functions replaces the Boolean functions. As at 1970 or thereabout, researchers made a request for the implementation of FHE. There was a high acceptance rate from the people. Now, anyone can apply it anywhere.

This project was widely acceptable. It made a researcher to attest to this with his publication. Fully Homomorphic Encryption needs more time for computation, even if its a small data.

FHE And Other Types of Encryption, Which Is Preferable?

Remember, the optimum priority of heads of companies is to safeguard data effectively. That is why they adopt FHE. It safeguards and computes data without decrypting it.

For instance, Google brought out a tool, that works on FHE. They design of this tool is such that, it computes data without revealing any confidential information. Also, Doctors can give medical reports without releasing the details of the patient. People prefer FHE due to is ability to conceal confidential informations from the public. It also rules off the compromise between data privacy and data usability. This makes both of them scalable.

Is It Safe To Use Fully Homomorphic Encryption ?

It records a high level of usability safety more than any other data protection forms. This is from the remarks of its users. However, different sectors can apply it for data security.

The storage of data in the cloud is a rising want of people. However, with the efficiency of FHE, it would stand out amongst other options. This is because, it overcomes many attacks effectively.

IBM in its note, said that the previous solutions of hiding the identity of data, limits the function of valuable patient data. Also, it can better the data-sharing protocols, increase sample sizes and increase learning. This is in relation to real-world data and clinical research.

In What Aspect Of Business Can We Use FHE?

The influence fully homomorphic encryption has on companies, helps in regulating data usage. It is important to regulate data usage, while safeguarding the customer’s data.

The special features of storing data on an encrypted platform, restricts it from any form of attack. However, the owner can still make use of it without hindrance. With this development, there is reduction in regulatory fines being paid by organizations. It also gives room for secure data monetization efforts.

Here, there is possibility of ensuring data sharing with intermediaries. This way, it reduces threats and ensures the adherence of regulations. Hence, this particular encryption propels the effort of carrying out research.

In Which Company Can One Obtain FHE Products?

As much as fully homomorphic encryption is beneficial, it isn’t wide spread. Some companies like Intel and Inpher offer such product. Intel is concerned with separation of data into sectors for easy computation. While, Inpher handles multiparty processing of data.

Now let’s look at IBM. It released its iOS toolkit in 2020. The idea behind this, is to improve the commercial value of FHE. Also, to put in check, its computation time and power. Most importantly, all these attributes made the company’s leaders to recommend FHE for target use cases. Health facilities and finance firms make go use of it.

The Potential Fully Homomorphic Encryption Exhibit

The wide unavailability of FHE will warrant people who wish to use it, to suspend it. But, in another way, some bodies are looking towards maintaining an equilibrium between safeguarding data and usability of data. This can change the situation. Most importantly, business owners should look out the best options. Then, check if it fits in to FHE, its present and future abilities.

The relationship between IBM and Fully Homomorphic Encryption

After a certain period, developers feel it is time for FHE to be accessible by interested customers. Even some companies like Microsoft and Intel have shown keen interest in it. However, in recent times, IBM made a release of its first homomorphic encryption services. It attracted a lot of attention to it. The development came with a lot of creative and prospective features. These features will aid companies to perform experiments.

Eric Maass, who is incharge of IBM, made a revelation. The revelation is to show the reason for increase in the company’s value on FHE.

Eric Maass believes that FHE is now fully set for customers to make use of it. This is after a decade of developing it. Its usability in a wide area has alsways been his worry. So now, clients can make use of it in a widespread manner. Also, some companies have shown their ability to utilize FHE. IBM is constantly setting up means to improve the FHE usability. The introduction of open source toolkit by IBM research aims at improving the development. In addition, in December, IBM security brought its first commercial FHE service.

An Illustration Of Fully Homomorphic Encryption

Using A Private Medical Data As A Case Study.

Case: The computation of medical statistics of lung cancer patients.

Challenge: Due to the HIPAA privacy rule, medical personnels cannot disclose confidential medical report to the outsider.

Solution: With the use of fully homomorphic encryption scheme, the data is encrypted. This way, they can carry out computation on it while it is safe.

Functionality: After the homomorphic encryption, the hospital sends the medical data out. It goes to the researcher’s cloud. The researcher can now process the encrypted data. When this is complete, he or she processes the result, decrypt it and disclose it in a plaintext. Throughout the operation, the data is under encryption. It will only undergo decryption at the result end. This also happens under the organization’s protection.

Pros of Fully Homomorphic Encryption

  • Unable to be compromised: Most times, we find data in an unsafe place. The ability for them to remain in a state of concealment, makes it outstanding. It encryption makes it withstand compromise.
  • No tradeoff between data usability and data privacy: The security of data is assured already. Introducing additional features is unnecessary. However, most features are basically for the analysis of data. use of any feature is done without jeopardizing the privacy of the data.
  • Safety from quantum attacks: The beauty of FHE is its ability to ward off quantum attacks.

Cons of Fully Homomorphic Encryption

  • Low performance level: When it comes to handling processing of high data, FHE is usually slow. Sometimes, its accuracy depreciates too. However, with time, it will become very scalable. Then, it can handle heavy computations. Nevertheless, it is still applicable to other technologies that are in line with increasing data privacy.
  • Still New And Developing: FHE is still not fully developed, as it is still emerging. It can’t carry out certain computations yet. However, its security of data is till very much active. Also, in its current state, the use cases that were not possible for computation, are not possible.

A perfect combination that can enhance privacy is FHE and secure multiparty computation. The both of them are very compatible. For instance, Inpher’s XOR Secret Computing Engine gives room for both secure multiparty computation and fully homomorphic encryption. Computation with private algorithms and verifications are all found in the use cases functioning with fully homomorphic encryption and multiparty computation.

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