# Secure and Privacy-Aware Blockchain Design: Requirements, Challenges and Solutions
## 5 Evaluation and Discussion
### Comparative Analysis
\begin{table}
\begin{tabular}{p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt}} \hline \hline
**Mechanism** & **Complexity** & **Scalable** & **Size Overhead** & **High Memory Cost** & **Efficiency** & **Computation Overhead** & **Communication Overhead** & **High Latency** \\ \hline Symmetric key Cryptography (DES), AES, RCS etc etc) & Low [58] & Yes [59] & Low [72] & Yes [58] & Yes [58] & Low [132] & Yes [58, 59] & Yes [58] \\ \hline Asymmetric key Cryptography (Eligant), RSA, etc. & High [127] & Yes [61] & High [133] & High [6, 128] & Yes [60, 128] & High [127] & Yes [134] & No [134] \\ \hline Homomorphic Encryption & Low [62] & No & Low [62] & No [62] & Yes [62, 63] & Low [62] & Low [62] & No \\ \hline Hash Function (MD5, SHA-1) &
\begin{tabular}{} \end{tabular} & No & High [136] & Yes [136] & Yes [135] & Low [136] & N/A & No \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._Homomorphic encryption allows mathematical operations on encrypted data by untrusted third party and ensures the privacy of sensitive data [137]. In [62], the authors present a transaction-privacy bitcoin framework by using homomorphic encryption that is efficient and less complex because it has small unit of time in terms of key generation, encryption, verification, and decryption. The proposed framework is secure and prevents the active attack, double spending attack, and passive attack but it does not ensure identity privacy. This technique has low computation overhead in terms of modular operations on data. The communication cost between the user and the third-party server is low. In [135], the authors discussed the Hash function that is simple and efficient. The complexity of hash function is O(N), where N is the size of the input data. It is computationally intensive due to large hash size for SHA-256 and SHA-512 algorithms [136]. In addition to privacy challenges on blockchain, the reader is referred to additional survey papers [1, 5], where authors summarize the limitations of consensus algorithms (e.g., proof of work, proof of stake, and delegated proof of stake etc.) and privacy challenges (e.g., transaction linkability, private key management, and malicious smart contract etc.) as well as their corresponding countermeasures. However, as it is proved in literature, full anonymity is not ensured in the bitcoin blockchain. Related to cryptographic aspects, another identified limitation is to deal with the high computational cost of ZK-SNARKS on the blockchain. In [60], a simulation has been conducted to test the computation cost of an authentication scheme using Elliptic Curve Cryptography to achieve efficiency, key security, and user anonymity. The experimental results show that it is secure against replay attacks and man-in-the-middle attacks. The main disadvantage of this approach is its complexity because of Elliptic Curve Cryptography. In [61], the authors propose a blockchain-based system to send data anonymously and securely. The proposed system achieves scalability and reduces communication overhead without latency. Security properties (e.g., data confidentiality and authentication) and user's privacy are also provided but the proposed system is limited to private permission blockchain. However, the proposed system presents several drawbacks related to system complexity, computational cost, and high storage overhead. Authors in [64] propose a system that ensures identity privacy, unlinkability during a fair exchange, and security on data. The proposed system is based on decentralized blockchain and smart contracts are used to enforce fair transaction exchange between parties. It reduces memory cost. However, it is not scalable and requires high communication overhead. Analysis of complexity and attack risks are also not provided. Table 3 summarizes our findings that are detailed below.