Hashcash Tree, a Data Structure to Mitigate Denial-of-Service Attacks
Mario Alviano
Abstract
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Mario Alviano
Abstract
Open-access reader
Client puzzle protocols are widely adopted mechanisms for defending against resource exhaustion denial-of-service (DoS) attacks. Among the simplest puzzles used by such protocols, there are cryptographic challenges requiring the finding of hash values with some required properties. However, by the way hash functions are designed, predicting the difficulty of finding hash values with non-trivial properties is impossible. This is the main limitation of simple proof-of-work (PoW) algorithms, such as hashcash. We propose a new data structure combining hashcash and Merkle trees, also known as hash trees. In the proposed data structure, called hashcash tree, all hash values are required to start with a given number of zeros (as for hashcash), and hash values of internal nodes are obtained by hashing the hash values of child nodes (as for hash trees). The client is forced to compute all hash values, but only those in the path from a leaf to the root are required by the server to verify the proof of work. The proposed client puzzle is implemented and evaluated empirically to show that the difficulty of puzzles can be accurately controlled.
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Client puzzle protocols are widely adopted mechanisms for defending against resource exhaustion denial-of-service (DoS) attacks. Among the simplest puzzles used by such protocols, there are cryptographic challenges requiring the finding of hash values with some required properties. However, by the way hash functions are designed, predicting the difficulty of finding hash values with non-trivial properties is impossible. This is the main limitation of simple proof-of-work (PoW) algorithms, such as hashcash. We propose a new data structure combining hashcash and Merkle trees, also known as hash trees. In the proposed data structure, called hashcash tree, all hash values are required to start with a given number of zeros (as for hashcash), and hash values of internal nodes are obtained by hashing the hash values of child nodes (as for hash trees). The client is forced to compute all hash values, but only those in the path from a leaf to the root are required by the server to verify the proof of work. The proposed client puzzle is implemented and evaluated empirically to show that the difficulty of puzzles can be accurately controlled.
Key concepts: Merkle tree, Hash function, Hash tree, Hash chain, Computer science, SHA-2, Double hashing, Cryptographic hash function