Deep Research

Blockchain Technology Unveiled: Inner Workings of Bitcoin, Ethereum, and Beyond Introduction Blockchain technology is a novel approach to distributed databases that enables multiple untrusted parties to agree on a single source of truth without a central authority. At its core, a blockchain is a distributed ledger composed of sequential blocks of transactions, where each block is cryptographically linked to the previous one. This chain of blocks—secured by cryptographic hashes, digital signatures, and consensus algorithms—ensures that once data is recorded and confirmed by the network, it becomes extremely difficult to alter retroactively without detection. Blockchains like Bitcoin (the first decentralized cryptocurrency) and Ethereum (the first major smart contract platform) have popularized this technology, and newer implementations such as Cardano, Solana, and Polkadot introduce further innovations in performance and capabilities. ...

Machine Learning Models for Cybersecurity Tasks Cryptography Models Differential Neural Cryptanalysis (ResNet CNN) Architecture & Task: Uses deep neural networks (often residual CNNs) as distinguisher models to aid cryptanalysis. For example, Gohr’s pioneering 2019 work trained a residual CNN to distinguish encrypted ciphertext pairs from random, improving classical differential cryptanalysis on block ciphers. Recent models incorporate advanced layers like residual connections and gated linear units (GLUs) to predict key bits from known plaintext–ciphertext pairs. The neural net takes pairs (or structures) of data and learns to infer partial key information or identify non-random patterns. ...