Data encryption is the method of transforming readable data into an unreadable format. This is done to protect the information from being accessed by unauthorized individuals. Unfortunately, most cybersecurity breaches are caused by human error. Therefore, there are different types of encryption to protect data, one of which is homomorphic encryption.
It allows computations to be performed on ciphertexts without needing to decrypt them. This article will explain a homomorphic encryption example.
What is Homomorphic Encryption?
Fifty-four percent of companies argue that their IT departments are not sophisticated enough to handle advanced cyberattacks. Hence, the importance of privacy-preserving technologies can help keep our data safe from prying eyes. For example, homomorphic encryption is a technology that can revolutionize how you process and share sensitive information. It allows computation on encrypted data. It makes it possible to process and analyze information without ever decrypting it, which helps keep your info safe from prying eyes.
While it has been around for a while, it is only recently that researchers have been able to develop issues that most traditional methods are based on mathematical problems that are easy to solve when you have the original unencrypted data. However, homomorphic encryption relies on issues that are much harder to solve without access to the original data.
Here is where recent advances in cryptography have come into play. Researchers have developed new algorithms that can handle more complex problems, making homomorphic encryption a viable option for businesses and organizations looking to protect their data.
With so much sensitive information being processed and shared online, finding ways to keep the data safe is more crucial than ever. And homomorphic encryption offers a promising solution for achieving this goal. It has several applications, including cloud computing, extensive data analysis, and machine learning.
How Does It Work?
Global spending on security products amounted to $125.2 billion in 2020. One such data security system is homomorphic encryption. It is transforming information so that it remains encrypted but still computable. It is done by breaking the data into parts and encrypting each segment separately. The resulting pieces can then be recombined and processed as if they were still in their original form.
One example of how homomorphic encryption could be used is in the medical field. Imagine that a patient’s medical records are stored on a secure server. These records could be accessed by doctors and other medical staff with the appropriate permissions, but they would remain encrypted and inaccessible to anyone without authorization. In this case, homomorphic encryption allows the patient’s records to be processed and viewed without revealing the actual data.
Another example is in the world of financial trading. When a trader makes a trade, the trade details are sent to a secure server for processing. If the transaction is successful, the server will send back confirmation to the trader. However, the server will send an error message if the trade is unsuccessful. In both cases, the trade details are encrypted and cannot be read by anyone except those with authorized access.
Conclusion
A homomorphic encryption example can help better understand how this technology works more practically. It assures that only the intended recipient can decrypt and read the information. Consequently, many organizations are turning to it to keep their data secure.
