This article introduces the fundamentals of encryption, compares symmetric (AES) and asymmetric (SM2) algorithms, clarifies the role of HTTPS as a protocol suite, distinguishes hash functions from encryption, and walks through a national‑standard mutual authentication flow using SM2 and SM4.
This article walks through the mathematics of Bloom filters, showing how to model false‑positive probability, derive optimal bit array size and hash‑function count, and apply the formulas to a 4‑million‑item dataset with concrete examples and performance tables.
This article explains how to use a Bloom filter backed by Redis bitmap and Roaring Bitmap sharding to efficiently filter 800 million OpenID queries, covering memory planning, hash function selection, code implementation, and performance‑tuned batch write strategies.
This article explains the motivation behind using filters to reduce database I/O, introduces Bloom filters and their bitmap implementation, discusses their limitations, then covers Counting Bloom filters and Cuckoo filters—including their hash structures, deletion support, performance trade‑offs, and practical improvements.
Learn the fundamentals of information security through a myth-inspired scenario, covering how symmetric and asymmetric encryption, message digests, and digital signatures ensure confidentiality, integrity, and authenticity when transmitting a simple invitation, and explore a practical secure email system design.
The article explains Bloom filters—a probabilistic, space‑efficient data structure using multiple hash functions on a bit array to answer set‑membership queries with controllable false‑positive rates, detailing their construction, query process, optimal parameters, and common uses such as URL deduplication, cache protection, and spam filtering.
This article provides a comprehensive introduction to cryptographic techniques, covering the goals of confidentiality, integrity and authentication, and detailing symmetric, asymmetric and hash algorithms, common implementations, their advantages and drawbacks, as well as key exchange methods and public key infrastructure.
This article clarifies the often‑confused concepts of encryption, digest (hash), and encoding, explains their definitions, typical algorithms, practical usage scenarios, and highlights their similarities and differences to improve communication among developers.
This article explains the concept, principles, implementation details, and practical applications of Bloom Filters, including formulas for optimal bit array size and hash count, Java code examples using Guava, and common use cases such as deduplication, web crawling, and spam filtering.
This article explains the concept, typical use cases such as preventing database misses and cache penetration, the underlying hash‑based implementation with examples, and shows how to deploy a Bloom filter using RedisBloom, providing a practical guide for handling huge data sets.
This article explains typical Java issues such as NullPointerException, demonstrates using spin locks for efficient multithreading, emphasizes low‑coupling design, shows how to diagnose CPU spikes with Linux tools and jstack, and describes why hash functions have O(1) lookup with collision‑resolution strategies.
The article explains how blockchain, introduced by Satoshi Nakamoto in 2008, uses cryptographic hash functions, Merkle trees, proof‑of‑work, and digital signatures to create an immutable, trust‑minimized ledger, compares naïve and validated coin models, and contrasts public versus private blockchains while forecasting massive future growth.
This comprehensive guide walks developers through the fundamental principles of blockchain, covering monetary trust, cryptographic primitives, Bitcoin's transaction model, block structure, proof‑of‑work mining, security challenges, alternative consensus mechanisms, and real‑world applications beyond cryptocurrency.
This article explains the fundamentals of hash functions and encryption algorithms, illustrates Google’s SHA‑1 collision breakthrough, describes the classification of cryptographic methods, presents a detailed end‑to‑end encryption/decryption scenario, and shows how Java’s built‑in APIs and libraries support these techniques for secure data handling.
This article explains how to select appropriate hash functions for different key types, compares Thomas Wang's integer mix function with MurmurHash for strings, and details rehash strategies, load factor thresholds, and value storage structures in hash tables.
The article explains that general‑purpose hash functions like MD5 and SHA families are fast and vulnerable to brute‑force attacks, while bcrypt’s deliberately slow, work‑factor‑adjustable design makes it a far more secure choice for storing passwords.
