Are encryption algorithms designed to hinder parallelization and if so why

Question

I’ve heard that some encryption algorithms are intentionally resistant to parallelization. Why is this the case? Does it improve security, or are there other reasons for this design choice?

Answer 1

Encryption algorithms are often designed to resist parallelization in specific aspects, depending upon their intended use and security objectives. This design decision can enhance security, impose operating limitations, or balance computing efficiency with immunity to attacks.

1. Reasons for Resistance to Parallelization

a. Security Against Cryptanalysis

• Preventing Parallel Attacks:
  Some cryptanalytic techniques, like brute-force attacks or side-channel analysis, benefit from parallel computation. Algorithms resistant to parallelization can slow down these attacks by requiring sequential processing.

• Sequential Dependency:
  Algorithms like PBKDF2 or bcrypt (used for password hashing) intentionally involve steps that depend on the results of prior steps. This ensures attackers cannot leverage massive parallel computing resources to speed up brute-force or dictionary attacks.

b. Increased Computational Effort

• Key Stretching:
  Key derivation functions (KDFs) like scrypt are designed to resist parallelism by using memory-hard functions, making it computationally expensive to perform many simultaneous guesses.

• Resource Intensity:
  By resisting parallelization, algorithms can impose high computational and memory costs, deterring attackers with limited resources.

c. Operational Constraints

• Serialized Output Requirements:
  In some scenarios, such as stream ciphers (e.g., RC4 or ChaCha20), the output depends on a state that evolves sequentially. This ensures the integrity and uniqueness of the generated keystream.

• Ensuring Predictable Timing:
  Some algorithms prioritize predictable timing or power consumption to avoid side-channel vulnerabilities. Allowing parallelism can complicate these safeguards.

2. Examples of Algorithms and Parallelization Resistance

Resistant to Parallelization

• PBKDF2 and bcrypt:
  Use iterative processes to enforce sequential execution.

• Scrypt:
  Employs memory-hard functions to limit the advantage of parallel processing.

Parallelizable Algorithms

• AES (Advanced Encryption Standard):
  Highly parallelizable due to its block-based design, making it suitable for hardware acceleration and bulk encryption tasks.

• RSA and ECC:
  Modular arithmetic in these asymmetric algorithms is often parallelizable, especially for large-scale computations.

3. Benefits of Parallelization Resistance

• Enhanced Brute-Force Resistance:
  Slows down attackers leveraging distributed systems or GPUs.

• Improved Password Security:
  Algorithms resistant to parallelization are ideal for password hashing, ensuring each guess takes substantial time and resources.

• Better Defense Against ASICs and GPUs:
  Custom hardware or GPUs are less effective when algorithms are designed to resist parallel execution.

4. Downsides of Parallelization Resistance

• Performance Trade-Offs:
  Resistance to parallelization can increase computational cost for legitimate users, especially in high-throughput systems.

• Inefficiency in Modern Architectures:
  Many modern CPUs and GPUs are optimized for parallel processing. Algorithms resistant to parallelization may underutilize these capabilities.

• Latency:
  Sequential execution may introduce delays in real-time or high-performance systems.

5. Balancing Parallelization and Security

Modern encryption schemes often balance these needs:

• For bulk data encryption, parallelizable algorithms like AES are favored.
• For password protection, sequential, memory-hard algorithms like bcrypt or scrypt are preferred.