The article classifies encryption algorithms into symmetric vs. asymmetric, block vs. stream, and reversible vs. irreversible, outlines the main algorithms such as AES, RSA, ECC, DES/3DES, and hash/MAC, and provides practical guidance for selecting the appropriate method in Java applications.
This article introduces the five most common encryption algorithms—MD5, SHA‑256, DES, AES, and RSA—explaining their classifications, security properties, typical use cases, and providing complete Java implementations for each, while also showing how they underpin HTTPS security.
This article introduces Hashcat, the world’s fastest password‑recovery tool, outlines its extensive feature set, provides the project’s GitHub address, and explains how to download, install, and run basic commands with common options for various hash types and attack modes.
This comprehensive guide explains digital signatures, encryption and decryption processes, symmetric and asymmetric cryptography, and compares common algorithms such as MD5, SHA‑1, HMAC, DES, 3DES, AES, RSA, and ECC, complete with Java code examples and usage scenarios.
This article explains the principles behind Simhash, covering the shortcomings of traditional hash functions, the use of cosine similarity, random projection for dimensionality reduction, locality‑sensitive hashing, random hyperplane hashing, implementation steps, query optimization with the pigeonhole principle, and the algorithm's limitations in short‑text scenarios.
The article compares four consistent‑hashing algorithms—Ketama’s ring with virtual nodes, Rendezvous’s highest‑random‑weight method, Google’s Jump Consistent Hash, and Maglev’s lookup‑table approach—evaluating their balance, monotonicity, stability, scalability, and time complexity, and concludes that Ketama and Jump offer the best overall trade‑off.
This article introduces Python’s hashlib module, explains the principles and characteristics of common hash algorithms such as MD5, SHA‑1, SHA‑224, SHA‑256, SHA‑384, and SHA‑512, demonstrates how to compute their digests with code examples, and shows simple key‑based encryption techniques.
This article explains the three main types of encryption—symmetric, asymmetric, and hash algorithms—detailing their principles, common examples such as DES, AES, RSA, ECC, MD5, SHA families, their strengths, weaknesses, and typical application scenarios.
This article explains the principles, characteristics, and performance trade‑offs of the consistent‑hash (ring‑hash) and jumpstringhash sharding algorithms used by DBLE, presents test results on variance, latency and data balance, and concludes why DBLE prefers jumpstringhash.
This article explains the concept of information fingerprints, compares traditional set‑equality methods, introduces the Simhash algorithm for high‑dimensional text similarity reduction, and demonstrates how partitioned 64‑bit fingerprints enable efficient duplicate detection on massive web data.
This study compares hash‑based, CNN‑based, and local‑feature methods for client‑side image similarity detection in e‑commerce, showing that while hash methods are fast and CNNs are accurate but costly, the Hessian‑Affine detector combined with SIFT descriptors delivers the optimal balance of computational efficiency, robustness to transformations, and high recall/precision for on‑device duplicate filtering.
Consistent hashing organizes the hash space into a virtual ring, allowing cache servers and objects to be mapped with minimal disruption when servers are added or removed, thereby reducing cache misses and backend load compared to traditional modulo‑based hashing.
