Unit 3: Hash Functions, Cryptography, and Digital Signatures in Blockchain

 

Unit 3: Hash Functions, Cryptography, and Digital Signatures in Blockchain

1. Hash Function in Blockchain

A hash function is a cryptographic algorithm that converts any input data into a fixed-size, unique string of characters (a hash value). In blockchain, hash functions are crucial for:

·         Immutability: Each block includes the hash of the previous block, creating an unbreakable chain. Any alteration to an old block's data changes its hash, invalidating the subsequent block and making tampering easily detectable.

·         Data Integrity: Hashes act as a "digital fingerprint." If the hash of data matches a known hash, the data is confirmed to be unaltered.

·         Mining (Proof of Work): Miners in PoW blockchains compute hashes to find a specific output, securing the network and adding new blocks.

·         Merkle Trees: Transactions within a block are summarized into a single Merkle Root hash, included in the block header, allowing efficient verification of transactions.

Good hash functions are deterministic, one-way (irreversible), collision-resistant (hard to find two inputs with the same hash), and exhibit an avalanche effect (small input change yields large hash change). Common examples are SHA-256 (Bitcoin) and Keccak-256 (Ethereum).

2. Patterns of Hashing Data

Hashing patterns refer to how hash functions are applied in systems:

·         Independent Hashing: Each data item is hashed individually.

·         Repeated Hashing: A hash is re-hashed multiple times (e.g., in Proof of Work).

·         Combined Hashing: Multiple data pieces are concatenated and hashed together.

·         Sequential Hashing: An existing hash is combined with new data and re-hashed to update a chain of integrity (like block linking).

·         Hierarchical Hashing (Merkle Trees): Data is arranged in a tree structure, with individual item hashes combined hierarchically to form a single root hash, enabling efficient verification of large datasets.

3. Uses of Hash Values

Hash values are vital for:

·         Data Integrity Verification: Confirming data hasn't been tampered with.

·         Password Storage: Storing hashes of passwords instead of plaintext for security.

·         Digital Signatures: A core component to ensure the integrity and authenticity of signed documents.

·         File Identification: Unique "fingerprints" for files, useful in malware detection and deduplication.

·         Blockchain Immutability and Proof of Work: Essential for the security and operation of blockchain networks.

4. Cryptography: Activities and Types

Cryptography is the science of secure communication in the presence of adversaries. Key activities include:

·         Encryption/Decryption: Converting readable data (plaintext) to unreadable (ciphertext) and back to ensure confidentiality using keys.

·         Hashing: Creating unique, fixed-size outputs for integrity and authentication.

·         Key Management: Securely handling cryptographic keys.

·         Authentication & Non-repudiation: Verifying identities and proving message origin/receipt.

·         Digital Signing: Cryptographically proving authenticity and integrity of digital content.

Types of Cryptography:

1.      Symmetric-key: Uses a single, shared secret key for both encryption and decryption. Fast but has key distribution challenges (e.g., AES).

2.      Asymmetric-key (Public Key): Uses a pair of keys – a public key for encryption (or signature verification) and a private key for decryption (or signing). Solves key distribution but is slower (e.g., RSA, ECC).

3.      Hash Functions: One-way functions for integrity, not secrecy (e.g., SHA-256).

5. Digital Signatures

A digital signature verifies the authenticity and integrity of digital messages using asymmetric cryptography. The sender:

1.      Hashes the document.

2.      Encrypts this hash with their private key (creating the signature).

3.      Sends the document and signature.

The recipient:

1.      Hashes the received document.

2.      Decrypts the signature using the sender's public key to get the original hash.

3.      Compares the two hashes. If they match, the document is confirmed authentic and untampered, and the sender cannot deny signing it (non-repudiation).

Case Study: Blockchain Techniques in the Medical Field

Blockchain offers solutions for data silos, privacy, and supply chain issues in healthcare. Here's a differentiation of four key initiatives:

1.      Ambrosus:

Focus: Supply chain integrity and traceability for pharmaceuticals using blockchain (AMB-NET) and IoT sensors. Records data like temperature and location to prevent counterfeiting and ensure product quality from manufacturer to patient.

2.      Connecting Care:

Focus: Improving interoperability and secure data sharing of Electronic Health Records (EHRs). Uses a permissioned blockchain with smart contracts to manage patient consent and data access permissions. Often stores hashes/metadata on-chain, with sensitive data off-chain.

3.      FarmaTrust:

Focus: Combating pharmaceutical counterfeiting and ensuring drug traceability. Uses a private/consortium blockchain to record the journey of every drug package from origin to patient, providing an immutable audit trail and alerting to unauthorized alterations.

4.      MedRec (MIT DCI Prototype):

Focus: Decentralized EHR management and medical research data, empowering patients with data control. An Ethereum-based prototype using smart contracts to manage access permissions for EHR metadata/hashes, facilitating secure, privacy-preserving research.

Differentiation Summary:

Feature

Ambrosus

Connecting Care

FarmaTrust

MedRec

Primary Focus

Supply Chain Integrity (Pharma)

EHR Interoperability & Sharing

Anti-Counterfeiting (Drugs)

Decentralized EHRs & Research

Core Technique

Blockchain + IoT Sensors

Permissioned Blockchain, Smart Contracts

Private/Consortium Blockchain

Ethereum-based, Smart Contracts

Main Problem Solved

Counterfeit drugs, product quality

Fragmented EHRs, data access

Counterfeit drugs, supply chain fraud

Patient data ownership, research access

Data on Chain

Sensor data, product IDs

Metadata/Hashes of EHRs, consents

Drug IDs, supply chain events

Metadata/Hashes of EHRs, permissions

 

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