When I started working on real systems that handle money, cards, and sensitive data, I quickly realized that cryptography is one of those topics everyone talks about but very few people truly explain in a simple way. Most explanations I found online were either too academic or too marketing driven. In real life, when you are building payment systems, APIs, or backend services, you need something more practical. You need to understand why things exist, not just how to use them.
This article is my attempt to explain cryptographic algorithms the same way I usually explain them to teammates, auditors, or junior developers. Not as a lecture, and not as documentation copied from standards, but as a calm one on one explanation based on real experience. Everything here is something I have encountered while working on production systems, PCI audits, and security reviews.
Before going deeper, I want to make one thing very clear. Any sample code shown in this article is not taken from my actual production projects. The code is created only to simplify the explanation and demonstrate the concept. Real systems require more controls, validations, and protections.
I will also reference NIST SP 800 57 throughout this article. This document focuses on cryptographic key management and is one of the most commonly referenced standards during security audits. Even if you are not preparing for an audit, its principles are very useful for engineers.
Why cryptography exists at all
At its core, cryptography exists because we do not trust the environment where our data lives or travels. Networks can be intercepted, databases can be leaked, systems can be compromised, and insiders can make mistakes. Once you accept this reality, cryptography stops feeling optional and starts feeling necessary.
In payment systems, this is very obvious. Card data, PIN values, cryptographic keys, and transaction messages must be protected. But even outside payments, the same risks exist. User passwords, API tokens, session identifiers, and private messages all need protection. Cryptography gives us different tools to solve different parts of this problem, and this is where many misunderstandings begin.
One algorithm does not solve everything. Hashing is not encryption. Encryption is not signing. Random numbers are not just random numbers. Each exists for a specific purpose, and using the wrong one in the wrong place often leads to serious security issues.
Hashing and why it is not encryption
Hashing is usually the first cryptographic concept developers encounter, especially when dealing with passwords. A hash function takes input data and produces a fixed length output. Whether the input is short or long, the output length stays the same. What makes hashing special is that it is designed to be one way. You can calculate the hash from the input, but you cannot realistically recover the input from the hash.
This is why hashing is ideal for passwords. When a user creates a password, the system should never store the actual password. Instead, it stores the hash of that password. When the user logs in, the system hashes the entered password again and compares the result with the stored hash. At no point does the system need to know the real password.
I have seen systems where developers encrypted passwords instead of hashing them. Their reasoning was that encrypted data is safe. The problem is that encryption requires a key, and if the application can decrypt the password, then anyone who compromises the application can also decrypt all passwords. Hashing avoids this entire risk because there is nothing to decrypt.
Salt and why it matters in real systems
If two users choose the same password, their hashes should not look the same. This is where salt comes in. A salt is random data added to the password before hashing. Each user gets a unique salt, so even identical passwords result in different hashes. This protects against precomputed attacks like rainbow tables.
While NIST SP 800 57 focuses on cryptographic keys, the same principles apply here. Sensitive material must be protected, randomness must be strong, and reuse must be avoided.
Example for illustration only:
string password = "MySecretPassword";
byte[] salt = GenerateSecureRandomSalt();
byte[] hash = Hash(password + Convert.ToBase64String(salt));In real applications, you always use proven libraries and recommended password hashing mechanisms.
Symmetric encryption and the real challenge behind it
Symmetric encryption is what most people imagine when they think about encryption. The same key is used to encrypt and decrypt data. Algorithms like AES fall into this category. Symmetric encryption is fast and efficient, which makes it suitable for encrypting large amounts of data.
In payment systems, symmetric encryption is everywhere. PIN blocks, sensitive fields, transaction data, and internal secrets are all protected using symmetric keys. The algorithm itself is usually not the problem. The real challenge is key management.
If both sides need the same key, how do you store it securely, distribute it safely, rotate it regularly, and make sure it is never exposed? NIST SP 800 57 spends a lot of time explaining the lifecycle of cryptographic keys because this is where most systems fail.
I have seen keys hardcoded in source code, stored in plain text configuration files, or reused for many years. In contrast, in well designed systems, keys are stored inside hardware security modules, and applications never see the raw key material. They only request cryptographic operations.
Example for demonstration only:
byte[] key = GetSymmetricKey();
byte[] encryptedData = EncryptData(data, key);
byte[] decryptedData = DecryptData(encryptedData, key);The strength of the system depends far more on how the key is protected than on the encryption algorithm itself.
Asymmetric encryption and why it changed everything
Asymmetric encryption uses two different keys, a public key and a private key. What one key encrypts, the other key decrypts. This model solves the key distribution problem because public keys can be shared openly while private keys remain secret.
This is the foundation of HTTPS, digital certificates, and secure communications on the internet. In real systems, asymmetric encryption is rarely used to encrypt large amounts of data because it is slow. Instead, it is used to protect symmetric keys or to sign data.
Signing is often confused with encryption. When data is signed using a private key, anyone with the public key can verify that the data has not been altered and that it came from the expected source. In payment and backend systems, request signing is critical to prevent tampering and impersonation.
NIST SP 800 57 clearly distinguishes between different key types and their purposes. Encryption keys, signing keys, and key agreement keys all have different roles and lifecycles.
Example for illustration only:
byte[] encryptedKey = EncryptWithPublicKey(secretKey, publicKey);
byte[] decryptedKey = DecryptWithPrivateKey(encryptedKey, privateKey);This approach allows secure systems to scale without sharing secrets directly.
Random number generation and why it is often underestimated
Random number generation is one of the most underestimated parts of cryptography. Keys, salts, nonces, initialization vectors, session identifiers, and activation codes all depend on randomness. If the randomness is predictable, everything built on top of it becomes weak.
I have reviewed systems where random values were generated using time based or predictable functions. From an attacker’s perspective, this makes guessing keys or tokens much easier. NIST provides guidance on approved random number generation mechanisms and emphasizes unpredictability and sufficient entropy.
In one real case, activation codes were generated using a weak random function. With enough attempts, valid codes could be guessed. Replacing it with a cryptographically secure random generator completely changed the security level without changing the feature itself.
Example for demonstration only:
byte[] randomBytes = GenerateSecureRandomBytes(32);That single decision can determine whether a system is resilient or fragile.
How these pieces work together in real applications
In real world systems, hashing, encryption, asymmetric cryptography, and random number generation are never used in isolation. They work together. Passwords are hashed, keys are generated using secure randomness, data is encrypted using symmetric keys, and keys are protected or exchanged using asymmetric techniques.
When auditors review systems, they do not only ask which algorithms are used. They ask how keys are generated, how long they are valid, who can access them, and how they are rotated or destroyed. This is why NIST SP 800 57 is referenced so often. It focuses on responsibility and lifecycle, not just algorithms.
Closing thoughts
Cryptography is not about being clever or using the newest algorithm. It is about discipline, consistency, and understanding why each tool exists. Most real world security failures come from misuse, not from broken algorithms.
I wrote this article the same way I explain things to people I work with. Calm, practical, and based on real experience. If you are building systems that handle sensitive data, I strongly recommend reading NIST SP 800 57 directly, not just for audits, but to develop the right mindset.
Security improves when understanding improves.
