Introduction

The world of blockchain is actively evolving, with new projects and technologies constantly bringing innovation to the industry.

The immense demand and popularity of cryptocurrencies became a challenge to the industry leaders such as Bitcoin and Ethereum, which were not developed with the expectation of such rapid scalability. The inability to scale quickly resulted in high gas prices, a problem that was addressed by developing sidechains and L2 projects. Unfortunately, this solution has created a new issue: fragmented liquidity.

Bridges, a solution often proposed to tackle this problem, have introduced their own set of issues by making wrapped tokens to represent an original asset on a different blockchain. However, this approach creates an attack vector for all involved networks. If an attack is targeted at a specific network or TVL (total value locked on a particular platform), these wrapped tokens can quickly become worthless. If a hacker issues new wrapped tokens instead of stealing locked ones, the situation will still be catastrophic: users' wrapped tokens will still lose their value, and the negative experience will undermine trust in the entire system.

Even if a pure zero-knowledge (ZK) bridge were to be built (one that eliminates the need for trusted validators), it would still face significant challenges. One such challenge includes creating and managing wrapped assets that must be stored in pools. These pools, and indeed networks themselves, are susceptible to attacks, including the infamous 51% attack that threatens the integrity of an entire network.

Vitalik Buterin has written extensively on the problems of interoperability and scalability in blockchain networks. He specifically warned about security issues with tokens wrapped by bridges and insisted that only native tokens should exist on their respective chains: [AMA] We are the EF's Research Team (Pt. 7: 07 January 2022).

The Kinetex team aligns with this viewpoint and proposes a system that refrains from intermingling assets between networks or issuing new wrapped tokens.

Another crucial aspect that highly affects cross-chain transactions is the Automated Market Makers (AMM) pools in DeFi trading. These pools provide an advantage by allowing users to automatically swap assets without waiting for other network participants. However, this approach comes with multiple critical problems, including price slippage and the potential for MEV (Miner Extractable Value) attacks. The latter occurs when miners collude with hackers to rob users. Another concern is the impermanent losses (IL) and the probable manipulations with prices of low-liquid pairs. Both are possible since AMMs rely on a closed ecosystem and operate according to the pool's formula.

Kinetex believes this approach is unsuitable for creating a robust and efficient cross-chain solution. It is especially true if you use a combination of a DEX and a bridge or a more complex route (for example, a combination of a DEX, a bridge, and another DEX). In that case, there is a chance that a transaction will not go through due to slippage or high gas fees and get stuck in the intermediate network, which will cause additional costs for withdrawing funds and restarting the transaction again, but at a different price.

In conclusion, Kinetex believes that omnichain systems are inefficient and insecure since all complex systems present a risk of attacks and increase both execution time and transaction costs.

Instead, Kinetex introduces an on-chain trading approach to move liquidity cross-chain, allowing native assets to be traded without leaving their respective ecosystems. With this approach, participants can conduct secure transactions directly with each other without creating wrapped assets or storing their original assets locked in a smart contract, thus saving time and money. Trading native coins within their respective network provides a secure future for those networks and all their participants.

Moreover, the Kinetex system does not require users to place trust in validators by employing decentralized proofs that anyone can provide using zero-knowledge technology (ZK will be discussed in more detail in the further description of the protocol).

The proposed peer-to-peer approach and the open-source trading smart contract allow resolvers to seamlessly create a fair market with customized trading strategies while keeping their developments private on the backend. The resolvers can also develop next-generation bots using machine learning and thoroughly analyze database sources using artificial intelligence. Thus, Kinetex enables resolvers to create a new generation of trading bots that further explore the boundaries of DeFi, acquire new technologies by analyzing trading strategies, and connect with the liquidity of centralized and traditional markets. Deep learning of big data can prevent potential attacks and track threats on a higher level, creating a truly decentralized market.