According to a recent report, Meta, formerly known as Facebook, plans to implement default end-to-end encryption in 2023. This is because Meta, a non-profit organization, considers encryption to be a basic human right and necessary for secure data exchanges. However, encryption algorithms deteriorate over time due to security flaws, putting data at risk. Encryption techniques are primarily used to prevent unauthorized third-party access to private data.
To prevent eavesdropping, the data is overlaid with an encryption key, resulting in data that is not the same for people who do not have access to the key. The Secure Hash Algorithm (SHA) and Advanced Encryption Standard (AES) algorithms are examples of standard algorithms that protect data and can withstand more advanced cyber-attacks. However, in light of emerging technologies such as block-chain, quantum computing, and cloud computing, traditional protocols are insufficient for ensuring data privacy. Meanwhile, researchers are devising methods to circumvent advanced code-cracking technologies, ensuring that big data remains secure. Following are some examples:
Quantum-proof Encryption:
Qubits, as opposed to conventional computing’s 0s and 1s, are used in quantum computers. As a result, the computing power is far superior to that of standard computers, including the ability to solve mathematical problems that underpin modern encryption algorithms. For decades, researchers have known that if a large-scale quantum computer could be built, it could do some pretty big calculations that would threaten the cryptosystems that we rely on today for security, says Dustin Moody, a mathematician at the US National Institute of Standards and Technology.
The quantum-proof encryption employs lattice-based cryptography, which employs massive grids and billions of individual points spread across thousands of dimensions. Moving along a set of random points would be required to break the code. It is nearly impossible to break the code unless you know the route.
Homomorphic Encryption:
Encrypted data must be decrypted to be viewed in its original form, and this process can make it vulnerable to breach. Homomorphic encryption provides a solution to these encryption flaws. It essentially entails masking the data with algebraic functions for data manipulation, allowing the data to remain encrypted while being used. To access the data, the person on the other end must use a private key in addition to the public key.
Homomorphic encryption is especially useful when it comes to protecting personal data without involving third parties, such as Google or companies that do not have a direct relationship with the data, in the transaction. This encryption is especially useful in the healthcare and defense industries, where personal data is extremely valuable.
Differential Privacy:
Unlike end-to-end encryption differential, privacy encryption employs mathematical noise to conceal the algorithm’s original calculations. The noise terms are large enough to obscure individual variables but small enough to reveal the pattern. Craig Gentry, a computer scientist from the United States, compares homomorphic encryption to a glovebox. Anyone can get their hands into it and manipulate it, but they won’t be able to get the final product out. When the finished product is ready, only the person who has the key can take it. The American Census Bureau is actively using this technique to protect its citizens’ data while also making it available to lawmakers for policy planning.
Block-chain Cryptography:
Cryptography for blockchain technology is undoubtedly the hottest area, with many players putting their money into it. Blockchain is one of the most vulnerable technologies due to its openness and the monetary stakes it holds. To authenticate transactions, block-chain technologies previously relied on protocols based on digital signatures.
These protocols need the use of a single key to sign in for all account-related transactions. Protocols such as ZK-Snark, an example of a zero-knowledge proof protocol, have recently been used to confirm a transaction without revealing the identity. ZoKrates, a toolbox for implementing the ZK-Snark protocol on Ethereum, assists users with verifiable computation on DApps. Earlier protocols only assisted with user identification; newer protocols add layers of software to track the entire course of transactions.
