Blog

21 March 2023

Store now decrypt later technology

"Store now decrypt later" technology, also known as "homomorphic encryption," is a technique used to secure data while it's being processed or stored, allowing data to be encrypted without compromising its utility. The basic idea behind this technology is that data can be encrypted in such a way that it can still be operated on without the need to decrypt it first.

In traditional encryption, data is encrypted before it's sent or stored, and it remains encrypted until it's decrypted. However, with homomorphic encryption, data can be encrypted, stored, and processed while still in its encrypted form. This allows the data to be stored securely, while still being able to perform calculations and operations on it without the need to decrypt it first.

Homomorphic encryption has applications in several fields, including healthcare, finance, and government. For example, it can be used to securely store and process medical records while maintaining patient privacy, or to protect sensitive financial data such as credit card numbers and bank account information.

One of the main challenges of homomorphic encryption is that it's computationally expensive, meaning that it requires a lot of processing power and time to perform operations on encrypted data. However, with recent advances in technology, researchers have been able to make significant improvements in the performance of homomorphic encryption, making it a more practical solution for real-world applications.

Background:

"Store now decrypt later technology" refers to a method of encrypting data in a way that allows it to be stored securely while remaining unreadable to unauthorized parties, and then decrypted later when access is required. This technology is also known as "deferred decryption" or "lazy decryption."

The idea behind this technology is to provide a more efficient way of storing and accessing encrypted data, particularly in situations where data needs to be accessed frequently. Instead of decrypting the data each time it is accessed, the data can be decrypted once and then stored in its decrypted form for future use.

One example of where this technology is commonly used is in cloud storage services. Cloud storage providers use this technology to store customer data in an encrypted form, which is then decrypted when the customer accesses it. This helps to ensure that the customer's data is protected from unauthorized access, while also making it easier for the customer to access their data quickly and efficiently.

Another example of where this technology is used is in email encryption. Emails can be encrypted using "store now decrypt later technology" to ensure that the contents of the email are secure while in transit and at rest. The email can then be decrypted when the recipient opens the email.

Overall, "store now decrypt later technology" provides a more efficient and secure way of storing and accessing encrypted data, and it is likely to become more prevalent as the need for secure data storage and transmission continues to grow.

Key Points:
  1. Encryption: Encryption is a process of converting plaintext into ciphertext, making it unreadable without the key. Homomorphic encryption is a type of encryption that allows data to be processed in its encrypted form.

  2. Processing encrypted data: With homomorphic encryption, data can be processed without decrypting it first. This means that sensitive data can be processed without being exposed to the risks of data breaches, hacking, and unauthorized access.

  3. Benefits: Homomorphic encryption provides several benefits, including the ability to keep sensitive data encrypted while it's being processed, and the ability to analyze data without revealing sensitive information.

  4. Applications: Homomorphic encryption has many applications, including secure cloud computing, secure data sharing, and secure machine learning. For example, it can be used to analyze medical data without revealing personal information, or to process financial transactions without exposing sensitive financial data.

  5. Performance: One of the main challenges of homomorphic encryption is that it can be computationally expensive, which can make it impractical for certain applications. However, researchers are working to improve the performance of homomorphic encryption algorithms.

  6. Future potential: Homomorphic encryption has the potential to revolutionize the way data is processed and analyzed, by allowing data to be securely processed in the cloud or other third-party environments. However, more research is needed to improve the performance and scalability of homomorphic encryption, and to develop new applications for the technology.

Example and Evidence:
  1. NIST Post-Quantum Cryptography Standardization: The National Institute of Standards and Technology (NIST) has been working on standardizing post-quantum cryptography algorithms since 2016. In 2020, they announced the finalists for the standardization process, which includes algorithms such as lattice-based cryptography, code-based cryptography, and hash-based cryptography.

  2. Google's New Hope: In 2015, Google announced a new encryption algorithm called "New Hope" that is designed to resist attacks from quantum computers. New Hope is a variant of lattice-based cryptography and is believed to be secure against quantum computers. Google has since open-sourced New Hope, making it available for others to use and test.

  3. IBM's Homomorphic Encryption: In 2019, IBM announced that it had successfully created a homomorphic encryption algorithm that is resistant to attacks from quantum computers. Homomorphic encryption allows data to be processed while still encrypted, which can be useful for privacy-preserving computations. IBM's algorithm is based on lattice-based cryptography and is believed to be secure against quantum computers.

  4. Microsoft's Kyber: Microsoft has also been working on post-quantum cryptography algorithms, and in 2018, they announced their own encryption algorithm called "Kyber". Kyber is a lattice-based cryptography algorithm that is designed to be fast and efficient while still being secure against quantum computers.

  5. QKD (Quantum Key Distribution): Quantum key distribution (QKD) is a technology that allows two parties to share a secret key that is secure against eavesdropping, even if the eavesdropper has a quantum computer. QKD uses the principles of quantum mechanics to ensure the security of the key exchange. While QKD is not a post-quantum cryptography algorithm, it is an example of a technology that is designed to be secure against quantum computers.

 Conclusion:

In conclusion, "Store now decrypt later" technology is a valuable tool for enhancing the security of sensitive data. By encrypting data at rest and delaying decryption until needed, the risk of unauthorized access to the data is greatly reduced. Additionally, this technology can be particularly useful in scenarios where sensitive data needs to be stored for extended periods of time, but only needs to be accessed infrequently.

As a cybersecurity provider, digiALERT can implement "Store now decrypt later" technology for clients who require it, providing an additional layer of protection for their sensitive data. By working with digiALERT, clients can rest assured that their data is being protected by the latest and most advanced security technologies available.

Read 217 times Last modified on 29 March 2023

Information

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