Blockchain technology revolutionized digital transactions through its fundamental principle of transparency - every transaction is visible and verifiable on the public ledger. However, this transparency creates a significant paradox: while it ensures trust and verification, it simultaneously compromises user privacy and creates vulnerabilities that malicious actors can exploit.
The first major challenge lies in the lack of confidentiality. Although blockchain transactions are pseudonymous, advanced analytics tools can easily trace transactions, potentially revealing participant identities [1]. This missing confidentiality makes blockchain interactions exploitable and leaves users vulnerable to risks, including frontrunning and leakage of private information. Such privacy concerns create a substantial barrier to widespread adoption, particularly for enterprises and consumers who require confidentiality in their financial dealings.
The second major challenge emerges from how blockchains order transactions. Block proposers have full control over which transactions to include and how to order them, leading to what is called Maximal Extractable Value (MEV). MEV is the maximum value that can be extracted from a proposed block by arranging and sequencing transactions. To maximize the additional value within a block, the block proposers strategically place their own transactions to enhance their profitability. [2] This rearrangement of transactions results in unexpected outcomes for the user. ****Since the outcome is different than what user expected, these MEV actions are called "MEV Attacks" or a “silent tax”. Below are the possible attacks that could happen:
Ultimately, MEV creates an unfair trading environment, where users pay hidden costs while block proposers extract profits.
To address these fundamental challenges of confidentiality and MEV exploitation, Fluton introduces a Privacy-Preserving Intent Settlement Mechanism (PRISM) leveraging encrypted intents. Encrypted intents enable privacy-preserving, MEV-resistant transactions by encrypting a user intent until execution (read more on intents in Union’s Intents Bridging article [3]). This is achieved through Fully Homomorphic Encryption (FHE), a technology that enables processing encrypted data without decrypting it [4]. This means with FHE, we are able to perform mathematical operations, such as addition and subtraction, over encrypted data without knowing what the actual data is.
There are two primary types of encrypted intents: