# Empirical Evaluation of Privacy Efficiency in Blockchain Networks: Review and Open Challenges
###### Abstract  
With the widespread of blockchain technology, preserving the anonymity and confidentiality of transactions have become crucial. An enormous portion of blockchain research is dedicated to the design and development of privacy protocols but not much has been achieved for proper assessment of these solutions. To mitigate the gap, we have first comprehensively classified the existing solutions based on blockchain fundamental building blocks (i.e., smart contracts, cryptography, and hashing). Next, we investigated the evaluation criteria used for validating these techniques. The findings depict that the majority of privacy solutions are validated based on computing resources i.e., memory, time, storage, throughput, etc., only, which is not sufficient. Hence, we have additionally identified and presented various other factors that strengthen or weaken blockchain privacy. Based on those factors, we have formulated an evaluation framework to analyze the efficiency of blockchain privacy solutions. Further, we have introduced a concept of privacy precision that is a quantifiable measure to empirically assess privacy efficiency in blockchains. The calculation of privacy precision will be based on the effectiveness and strength of various privacy protecting attributes of a solution and the associated risks. Finally, we conclude the paper with some open research challenges and future directions. Our study can serve as a benchmark for empirical assessment of blockchain privacy. ao 2021 26 July 2021 29 July 2021 2  
through public verification and storage of the records, hence the data on a public blockchain is readily available for anyone to download and access. As a result, a risk of privacy breach of the user involved in a transaction exists. Privacy can be defined as the ability of a user to seclude themselves from sharing their confidential information and/or choose the extent of information disclosure in a shared setting. In blockchain networks, the term \"privacy\" is used for two aspects, i.e., user privacy and data privacy of the transactions. These two types of transaction privacy in blockchains are elaborated below:  
1. User Privacy (Anonymity)  
User privacy is the ability to convert the real identity of a blockchain user into something that cannot be identified, and further ensuring that the original identity also remains unobtainable [10]. This type of privacy is more commonly known as anonymity. It conceals the real-world identity of the user by masking the users' real network address with a computer-generated address. 2. Data Privacy (Confidentiality)  
Hiding the contents of a transaction keeps blockchain data privacy intact. Data privacy is also referred to as confidentiality. At the most basic level, the data contents in a transaction are usually encrypted to maintain confidentiality in the network. Maintaining data confidentiality ensures that the transaction contents are free from unauthorized accessing, meddling and altering. Despite all the glorious features of the blockchains, the tendency of these systems towards privacy disclosure is a worrisome issue nowadays [11]. Some may argue that the data on blockchain is encrypted and thus user assets are protected. However, privacy does not only refer to the data in blockchains, it also refers to protecting identity of participants in the network [12] as mentioned earlier. Deanonymization [13] of users in the network is a huge privacy issue. Analyzing transaction relationships, patterns, time, and links is possible. This creation of links between various transactions makes it convenient to trackback to the head node and determine the identities of transaction initiator and receiver. The details in this regard are given in [14] and are beyond the scope of this paper. According to [15], leakage of an individual's identity in blockchain results in disclosure of its corresponding transaction information. Therefore, using a blockchain jeopardizes the assets of a user by opening these to unauthorized exposure.