Computational hardness describes the difficulty of solving a mathematical problem, measured by the resources required for a computer to find a solution. In cryptography and blockchain, problems with high computational hardness are selected to secure systems, rendering them resistant to brute-force attacks. The security of many cryptographic algorithms relies on the assumption that certain problems are practically impossible to solve within a reasonable timeframe. This property forms the foundation of cryptographic security.
Context
Discussions surrounding computational hardness often appear in news related to advancements in quantum computing and their potential impact on current cryptographic standards. Researchers and developers are exploring post-quantum cryptography to address future threats to blockchain security. The ongoing pursuit of new algorithms with demonstrable computational hardness against advanced computing capabilities remains a critical area of research and development.
By introducing a security definition based on logical independence, this breakthrough achieves non-interactive, transparent zero-knowledge proofs with perfect soundness, eliminating the need for trusted setups.
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