Final version of Nescience

rlog/2023-08-28-Nescience.mdx

@@ -443,3 +443,49 @@ To achieve seamless interaction between public and private states, composability
 | **Ring Signatures & CoinJoin**            	|                                  Incorporate ring signatures and CoinJoin protocols to mask transaction details and mix transactions collaboratively.                                  	|   	|
 
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+# Goal 6: Integration of DeFi Protocols with a Privacy-Preserving Framework
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+The primary aim of Goal 6 is to weave key DeFi protocols, such as AMMs and staking, into a user-centric environment that accentuates privacy. This endeavor comes with inherent challenges, especially considering the heterogeneity of existing DeFi protocols, predominantly built on Ethereum. These variations in programming languages and VMs exacerbate the quest for interoperability. Furthermore, the success and functionality of DeFi protocols is closely tied to liquidity, which in turn is influenced by user engagement and the amount of funds locked into the system.
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+## <ins> Strategic Roadmap for Goal 6 </ins>
+
+1. _** Pioneering Privacy-Centric DeFi Models: **_ Initiate the development of AMMs and staking solutions that are inherently protective of users' transactional privacy and identity.
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+2. _** Specialized Smart Contracts with Privacy: **_ Architect distinct smart contracts infused with privacy elements, setting the stage for secure user interactions within this new, confidential DeFi landscape.
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+3. _** Optimized User Interfaces: **_ Craft interfaces that resonate with user needs, simplifying the journey through the private DeFi space without compromising on security.
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+4. _** Tackling Interoperability: **_ 
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+    * Deploy advanced bridge technologies and middleware tools to foster efficient data exchanges and guarantee operational harmony across a spectrum of programming paradigms and virtual environments.
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+    * Design and enforce universal communication guidelines that bridge the privacy-centric DeFi entities with the larger DeFi world seamlessly.
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+5. _** Enhancing and Sustaining Liquidity: **_
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+    * Unveil innovative liquidity stimuli and yield farming incentives, compelling users to infuse liquidity into the private DeFi space.
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+    * Incorporate adaptive liquidity frameworks that continually adjust based on the evolving market demands, ensuring consistent liquidity.
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+    * Forge robust alliances with other DeFi stalwarts, jointly maximizing liquidity stores and honing sustainable token distribution strategies.
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+6. _** Amplifying Community Engagement:**_ Design and roll out enticing incentive schemes to rally users behind privacy-focused AMMs and staking systems, thereby nurturing a vibrant, privacy-advocating DeFi community.
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+Through the integration of these approaches, we aim to achieve Goal 6, providing users with a privacy-focused platform for engaging effortlessly in core DeFi functions such as AMMs and staking, all while effectively overcoming the obstacles related to interoperability and liquidity concerns.
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+
+# Summary of the Architecture
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+In our quest to optimize privacy, we're proposing a Zero-Knowledge Virtual Machine (Zkvm) that harnesses the power of Zero-Knowledge Proofs (ZKPs). These proofs ensure that while private state data remains undisclosed, public state transitions can still be carried out and subsequently verified by third parties. This blend of public and private state is envisaged to be achieved through a state tree representing the public state, while the encrypted state leaves stand for the private state. Each user's private state indicates validity through the absence of a corresponding nullifier.
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+Private functions' execution mandates users to offer a proof underscoring the accurate execution of all encapsulated private calls. For validating a singular private function call, we're leaning into the kernel-based model inspired by the ZEXE protocol. Defined as kernel circuits, these functions validate the correct execution of each private function call. Due to their recursive circuit structure, a succession of private function calls can be executed by calculating proofs in an iterative manner. Execution-relevant data, like private and public call stacks and additions to the state tree, are incorporated as public inputs.
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+Our method integrates the verification keys for these functions within a merkle tree. Here's the innovation: a user's ZKP showcases the existence of the verification key in this tree, yet keeps the executed function concealed. The unique function identifier can be presented as the verification key, with all contracts merkleized for hiding functionalities.
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+We suggest a nuanced shift from the ZEXE protocol's identity function, which crafts an identity for smart contracts delineating its behavior, access timeframes, and other functionalities. Instead of the ZEXE protocol's structure, our approach pivots to a method anchored in the security of a secret combined with the uniqueness from hashing with the contract address. The underlying rationale is straightforward: the sender, equipped with a unique nonce and salt for the transaction, hashes the secret, payload, nonce, and salt. This result is then hashed with the contract address for the final value. The hash function's unidirectional nature ensures that the input cannot be deduced easily from its output. A specific concern, however, is the potential repetition of secret and payload values across transactions, which could jeopardize privacy. Yet, by embedding the function's hash within the hash of the contract address, users can validate a specific function's execution without divulging the function, navigating this limitation.
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+Alternative routes do exist: We could employ signature schemes like ECDSA, focusing on uniqueness and authenticity, albeit at the cost of complex key management. Fully Homomorphic Encryption (FHE) offers another pathway, enabling function execution on encrypted data, or Multi-Party Computation (MPC) which guarantees non-disclosure of function or inputs. Yet, integrating ZKPs with either FHE or MPC presents a challenge. Combining cryptographic functions like SHA-3 and BLAKE2 can also bolster security and uniqueness. It's imperative to entertain these alternatives, especially when hashing might not serve large input/output functions effectively or might fall short in guaranteeing uniqueness.