The 5 Issues with Homomorphic Encryption

Introduction

Homomorphic encryption is a technique that allows data to be encrypted and processed without needing to be decrypted. This has the potential to enable secure computation in situations where sensitive data needs to be processed or shared, such as in healthcare or finance.

However, there are several challenges associated with homomorphic encryption that limit its practical applicability. In this blog post, we will discuss some of the key problems associated with it.

Performance

Homomorphic encryption is computationally expensive, and the overhead can be significant. This is due to the fact that computations need to be performed on encrypted data, which requires additional processing time. As a result, homomorphic encryption may not be feasible for large datasets or real-time processing.

Key Management

Homomorphic encryption requires secure key management, which can be challenging. The keys used for encryption and decryption must be kept secret and secure, and this can be difficult to achieve in practice. In addition, key management becomes more complex as the number of parties involved in the computation increases.

Limited Functionality

Homomorphic encryption is not suitable for all types of computations. Certain operations, such as sorting and searching, are particularly difficult to perform on encrypted data. As a result, there are limitations on the types of applications for which homomorphic encryption can be used.

Complexity

Homomorphic encryption is a complex technology that requires specialized knowledge and expertise to implement and use effectively. As a result, it may not be accessible to all organizations, particularly smaller ones with limited resources.

Trade-offs

There are trade-offs between security and performance in homomorphic encryption. In order to achieve better performance, some security features may need to be sacrificed, which can compromise the security of the system.

Conclusion

Homomorphic encryption is a promising technology that has the potential to enable the secure computation of sensitive data. However, there are several challenges associated with it that need to be addressed before it can be widely adopted. Researchers and developers are working to address these challenges, and it will be interesting to see how the technology evolves in the coming years.