## 3 Security Implications and Fundamental Approaches of Blockchain-Based Data Storage Methods
### The Role of Cryptographic Methods in Blockchain-Based Data Storage Systems
#### 3.2.9 Security vs. Performance Trade-Offs in Cryptographic Techniques  
Ensuring the security of blockchain-based storage requires employing cryptographic techniques that offer strong confidentiality, integrity, and authentication. However, these techniques vary in their computational overhead, which affects processing time, CPU utilization, and memory efficiency. Understanding the trade-offs between security and performance is essential when selecting the appropriate cryptographic approach for real-world applications. To provide a structured evaluation, Table 7 presents a comparative analysis of cryptographic techniques based on their security level, computational overhead, performance impact, and practical use cases. This analysis allows us to assess the balance between cryptographic robustness and system efficiency. \begin{table} \begin{tabular}{p{113.8 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline
**Cryptographic Technique** & **Security Level** & **Computational Overhead** & **Performance Impact** & **Use Cases** & **References** \\ \hline Asymmetric Encryption (RSA, ECDSA, Ed25519) & High & High due to key size and modular exponentiation & Slow for large-scale transactions, high processing cost & Digital signatures, secure authentication, blockchain consensus mechanisms & [114; 126; 127; 128] \\ \hline Symmetric Encryption (AES-256, ChaCha20) & High & Low, optimized for speed and efficiency & Fast and efficient, suitable for real-time processing & Encrypted storage, secure messaging, VPN encryption & [117; 122; 123; 124; 129] \\ \hline Zero-Knowledge Proofs (ZKP–SNARKs, STARKs) & Very High & Very High, requires complex proof generation & Slows down authentication due to proof verification time & Anonymous transactions, identity verification, privacy-focused blockchain applications & Anonymous transactions, identity verification, [56; 109; 115; 130; 131; 132] \\ \hline Homomorphic Encryption (Fully Encryption—FHE) & Very High & Extremely High, impractical for real-time operations & Extremely slow, impractical for large-scale blockchain storage & Cloud computing, privacy-preserving smart contracts & [120; 133; 134; 135; 136] \\ \hline Hashing Mechanisms (SHA-256, Keccak, Blake2) & Medium & Low, designed for quick computation & Minimal impact, designed for rapid verification & Blockchain transaction integrity, data verification, proof-of-work mechanisms & [16; 23; 24; 25] \\ \hline \end{tabular}  This comparative evaluation highlights key trade-offs in cryptographic techniques: Asymmetric Encryption (RSA, ECDSA, Ed25519)
* Offers strong security but incurs high computational overhead due to modular exponentiation. * Slower than symmetric encryption, making it less suitable for large-scale transactions. Symmetric Encryption (AES-256, ChaCha20)
* Designed for speed and efficiency, offering high security with low processing costs. * Used extensively for secure storage and fast encrypted communication. Zero-Knowledge Proofs (ZKP-SNARKs, STARKs)
* Provide privacy-preserving authentication but require significant computation. * Proof generation and verification are resource intensive, slowing down transactions. Homomorphic Encryption (FHE)
* Enables computations on encrypted data, offering maximum security. * Extremely high resource consumption makes it impractical for large-scale blockchain storage. * Lightweight and efficient, designed for rapid data integrity verification. * Low computational overhead, making it ideal for blockchain transaction verification. This evaluation demonstrates that higher security often comes with a significant performance cost. FHE and ZKP offer advanced security but impose high computational