Encryption

What is encryption?

Encryption protects sensitive data by converting it into a coded format that can only be read by someone with the proper decryption key. In the context of mobile security, encryption safeguards data both at rest (stored on the device) and in transit (sent over networks). This prevents unauthorized access and ensures that even if data is intercepted, it cannot be deciphered without the decryption key.

Summary

Mobile app data encryption involves converting sensitive data into a secure format that is only accessible by those with the correct decryption key. It ensures data protection when it is being sent over a network and/or when it is stored on the device.

It is generally recommended to use peer-reviewed, standardized encryption algorithms such as Advanced Encryption Standard (AES) and Rivest–Shamir–Adleman (RSA) because in-house algorithms may not be as resilient and robust as them.

Encryption is essential for protecting information from unauthorized access. By transforming readable data into an unreadable format, encryption ensures that only authorized parties with the correct key can access the original information. Often confused to be similar, encryption transforms data using keys to ensure confidentiality during transmission or storage while obfuscation obscures data without altering it to protect software.

Deep dive

How encryption works

Encryption transforms readable data (called plaintext) into an unreadable format (called ciphertext) to protect it from unauthorized access using encryption algorithms. Common encryption algorithms include AES (Advanced Encryption Standard), RSA (Rivest-Shamir-Adleman), and DES (Data Encryption Standard).

Encryption algorithms use mainly two types of keys to perform the transformation:

Symmetric key: The same key is used for both encryption and decryption.
Asymmetric key: Uses a pair of keys—a public key for encryption and a private key for decryption.

There are two kinds of encryption algorithms:

Symmetric encryption: To encrypt data, you input plaintext into the symmetric encryption algorithm along with the shared secret key. As output, you get ciphertext. Say you receive this encrypted data and want to read it now. To do so, you input the ciphertext into the decryption algorithm (the same as the encryption algorithm) and the same shared key. The resultant data is readable plaintext.
Asymmetric encryption: Asymmetric encryption differs in the sense that you share the key used to encrypt the plaintext publicly but keep the decryption key private. Similar to symmetric encryption, you enter plaintext and the public encryption key into the encryption algorithm to get ciphertext. To decrypt this ciphertext, you input the ciphertext along with the private decryption key into the algorithm to obtain plaintext.

Symmetric encryption	Asymmetric encryption
Uses the same key for encryption and decryption.	Uses a public key for encryption and a private key for decryption.
Example: AES encrypts data in storage and transit.	Example: RSA uses key pairs for secure communication.
Suitable for encrypting large volumes of data because it’s fast.	Used for key exchange, digital signatures, and securing communication channels like SSL/TLS for HTTPS connections.
Faster because of its simpler mathematical operations in processing, like XOR operations and bit shifts.	Slower because of intensive operations like modular exponentiation and prime number factorization.

Real-world applications

Secure communication: Encryption is used to secure messages sent over the internet, such as emails and instant messages.
Data protection: Sensitive data stored on devices or in the cloud is encrypted to prevent unauthorized access.
Authentication: Encryption is used in various security protocols to verify the identity of users and devices.

Data encryption vs. data obfuscation

Data encryption transforms data like your user’s credentials into a secure format that can only be read or decrypted with the correct cryptographic key. It uses mathematical algorithms to scramble data, making it inaccessible without the appropriate key.

On the other hand, data obfuscation masks your data by altering its appearance or structure to prevent unauthorized users from understanding it. While it does not necessarily involve complex mathematical algorithms, it protects data. One of the key differences is that obfuscation can be reversed without needing a key or understanding an algorithm by using a large language model (AI LLM).

Code encryption vs. code obfuscation

Code encryption secures your app data and algorithms by rendering them unreadable without the decryption key. It uses cryptographic algorithms to transform data into ciphertext. Because decryption uses mathematical algorithms, it employs multiple CPU cycles to decrypt the code, making it a bit slower.

On the other hand, code obfuscation protects app logic by altering code appearance and structure without affecting its functionality. It uses techniques like renaming variables, changing the code flow, or inserting dummy code. Obfuscation safeguards the app’s intellectual property and prevents unauthorized access to the codebase. Unlike encryption, an obfuscated code can be executed with minimal overhead.

Encryption vs. cryptography

Encryption is a subset of cryptography. While encryption specifically refers to the process of converting plaintext into ciphertext (secure form), cryptography is the broader field that encompasses not only encryption and decryption but also techniques like hashing and digital signatures. Cryptography includes the study of secure communication techniques that allow only the sender and intended recipient of a message to view its contents.

What makes a strong encryption algorithm?

Complexity and key length: Longer keys generally provide higher security as they are harder to crack using brute force methods. For instance, AES offers key sizes of 128, 192, or 256 bits, with 256-bit AES being one of the strongest.
Resistance to cryptanalysis: A robust algorithm should withstand attempts to break it using known cryptographic attack methods.
Randomness: Good encryption algorithms produce ciphertext that appears random, with no discernible patterns that attackers could exploit.
Standardization and peer review: Algorithms standardized by organizations like the National Institute of Standards and Technology (NIST) and undergoing extensive peer review are generally more reliable and resilient than non-peer-reviewed algorithms.

Examples

E-commerce transactions: Mobile shopping apps use SSL/TLS encryption to secure the transmission of financial data and personal information during checkout, protecting credit card numbers and personal details from MITM attacks.
Banking apps: Mobile banking apps encrypt user credentials and transaction details at rest and in transit to prevent unauthorized access. Doing so also ensures that financial transactions remain confidential and tamper-proof.
Cloud storage apps: Services like Dropbox and Google Drive encrypt files stored and shared on their platforms, both at rest and in transit.
VPN services: Virtual Private Network (VPN) apps encrypt internet traffic from mobile devices, creating a secure tunnel to a remote server on unsecure or public networks.
Secure messaging apps: Apps like Signal and WhatsApp use end-to-end encryption to ensure that messages can only be read by the sender and the intended recipient to prevent eavesdropping and interception.

History

Thousands of years ago, ancient Greeks and Romans used simple ciphers to encrypt. But after World War II and the introduction of public-key cryptography in the 1970s, encryption became critical to modern computing. As mobile computing rose in the late 1990s and early 2000s, encryption became important to protect the sensitive information stored on mobile devices and transmitted across networks. Today, encryption in mobile apps is driven by regulatory requirements, growing threats, and technological advancements.

Future

Recent advancements in technology and shifts in regulatory frameworks significantly affect mobile app encryption. AI-driven systems can analyze and adapt to threats in real time, enhancing data protection strategies. AI technologies can also be used to develop sophisticated methods to break encryption, reducing the time to crack encryption.

Quantum computers are also a concern, as they could theoretically break many of the cryptographic protocols currently used almost instantaneously. In response, researchers are developing quantum-resistant or post-quantum cryptographic methods that quantum computers cannot easily break. On the regulatory front, global standards and laws such as the GDPR in Europe and the CCPA in California are pushing for stronger data protection measures, including mandatory encryption of certain types of data.