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Ontology’s VBFT Algorithm sets new standard for blockchain consensus

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Ontology’s VBFT Algorithm sets new standard for blockchain consensus
Source: Pixabay

Ontology introduced its VBFT consensus algorithm last year and the project has continued to build momentum over the past several months. This is big news in the world of blockchain as the PoWand BFT consensus algorithms are what most mainstream public chains are using today.

Ontology hopes that the VBFTalgorithm will replace those commonly used, as they believe they have solved some of the major problems that lie within them. VBFT improves on the performance and scalability of public chains all while guaranteeing the randomness and fairness of a consensus network.

Other algorithms have been known to cause problems that hinder both the performance and the scalability of public chains.

Ontology’s improved platform will help dApp developers harness their creativity to its maximum potential and remove limitations imposed by inefficient algorithms with poor performance.

As the dApp developers lie at the center of the blockchain ecosystem, Ontology believes that the changes they are implementing will provide greater flexibility and further the ability of the developers to create new and innovative applications.

Constant improvements are being made to VBFT, and large-scale and long-term practices are in progress to track the performance of this new consensus mechanism.

Currently, the unreliability of nodes and the instability of communication between nodes suggests a problem with most consensus algorithms.

That problem is consistency. However, with Ontology’s new consensus algorithm, multiple unreliable node groups can be built into a reliable distributed system to achieve stability of data sets and improve system reliability. The blockchain, a decentralized peer-to-peer network, relies on the consensus algorithm to enable the order of transaction processing among the dispersed nodes.

The consensus algorithm also provides functionality for the incentive [i.e. mining] and governance models of the system.

Consensus algorithms have different fault tolerance capabilities and can be classified as Crash Fault Tolerance [CFT] or Byzantine Fault Tolerance [BFT] based on their node failure response. The CFT algorithm only ensures the reliability of the distributed system when nodes have downtime; when nodes violate consensus protocol, reliability is compromised.

For these reasons, the CFT algorithm is more applicable in the closed distributed system of the enterprise. With the BFT algorithm, so long as errors occur within a pre-defined ratio of nodes, the system is reliable. As a result, BFT-based algorithms, such as Ontology’s VBFT, are more suitable for the open distributed systems of public blockchains.

The consensus algorithm can further be divided into three types: synchronous, semi-synchronous, and asynchronous. A synchronous consensus algorithm requires that messages within a system can reach all nodes within a known amount of time. Naturally, it is mainly used in networks of limited scale.

An asynchronous algorithm removes the condition of messages reaching all nodes within a certain timeframe. However, asynchronous algorithms present problems guaranteeing the final result of consensus. For this reason, asynchronous algorithms are inefficient and have limited applications in this area.

A semi-synchronous algorithm, as the name suggests, ensures a relationship exists between the probability and delay for messages reaching consensus nodes within a set time. Today, most mainstream blockchains, including Ontology’s VBFT, are based on a semi-synchronous network model.

So, what is VBFT exactly?

VBFT is a new consensus algorithm that combines PoS (Proof of Stake), VRF [Verifiable Random Function], and BFT. VBFT is the core consensus algorithm of the Ontology Consensus Engine. Ontology’s core network is comprised of two main components.

The consensus network consists of the consensus nodes that are responsible for maintaining the blockchain, generating blocks, distributing consensus blocks to synchronous node networks, and overseeing transaction requests.

The second component of Ontology’s core network is the consensus candidate network which remains synchronized with the consensus network and continuously updates the consensus blocks on the blockchain. This all happens in real time which helps Ontology achieve top performance without sacrifice.

The candidate networks also validate consensus blocks, monitor the consensus network status, and assist in managing the Ontology network. It is also important to note that the size of the consensus network is managed through a consensus network smart contract which is beneficial for both the producer and consumers of this technology.

VBFT works by first selecting consensus candidate nodes within the Ontology network. Block verification and confirmation nodes are set, and then consensus is ultimately completed by aselected node group.

This ensures that theplatform always provides sufficient randomness and fairness to the users involved. All nodes in the network eventually receive the consensus result of the confirmation node before starting a new round of consensus. This ensures that the algorithm runs smoothly, quickly, and continuously.

Ontology’s consensus network is built by the Ontology Consensus Management Smart Contract, which runs permanently on the network. It provides regular updates to the node list in the consensus network and updates the VBFT algorithm. This provides the user with an up to date experience every time they use the platform.

After testing the VBFT algorithm, Ontology produced results that surpassed the results of other mainstream public chains in terms of efficiency, consensus confirmation time, resource consumption, and manageability.

Their network also contained the fewest malicious nodes. In April of this year, Ontology improved the network by increasing the number of consensus nodes from seven to eight.

Development of mainstream consensus algorithms continues to follow a trend to improve the performance, scalability, and decentralization of public blockchains. Ontology’s VBFT consensus has similar goals and has already made significant strides in improving the effectiveness and performance of blockchain ecosystems.

It is clear, with all the work that has gone into Ontology, this high-performance consensus algorithm is certainly ready to meet the needs of all businesses.

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Guest Post

Balancing Cypherpunk Principles and UX With Multi-Party Computation

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Balancing Cypherpunk Principles and UX With Multi-Party Computation
Source: Pixabay

One of the fascinating, and frustrating, aspects of the broader cryptocurrency space is the prevalence of trusted third-parties in an ecosystem built on the notion that trusted third parties are security holes. From honeypot exchanges to custodial services with “bank-level encryption,” much of the crypto ecosystem is non-representative of its origins.

Without diving into the adverse outcomes of these third-parties in the ecosystem, of which there are many, one of the underlying frictions of centralized security is the inherent trade-off between security and user experience [UX].

The crypto landscape is esoteric enough as it is, let alone requiring users to manage their own keys and understand concepts like GAS on Ethereum. In fact, new user onboarding was named as the biggest obstacle to dapp development by projects on Ethereum. While there have been strides made in UX among many crypto products, ranging from DeFi tools to wallet interfaces, there is much work to be done.

The daunting task of converging security and UX into a safe and user-friendly experience has received a glimmer of hope in recent months, however, due to a unique subfield of cryptography–secure multi-party computation [sMPC].

A Wave of sMPC Innovation

The core concept of sMPC is to collectively derive a unique computation from a subset of individual fragments like non-trusting computers. Imagine a puzzle with individual entities, each holding a piece, and the final image only materializing after a specific threshold of pieces have been put together.

MPC has been lauded as the next fuel for innovation in onboarding users to crypto by reducing a significant portion of the barrier to entry — mainly key management.

“Ultimately, using sMPC, we can realize the separation in data of the right to use and the right of use, and directly calculate results on multi-source and heterogeneous ciphertext data,” detailed ArpaChain CEO, Felix Xu, in a ChainNode AMA. ArpaChain has emerged as one of the leaders in sMPC globally, and already has a functioning product on its testnet.

Their insights and innovation into sMPC represent a broader initiative to reconcile the issues of security vs. UX.

At a high level, sMPC empowers users to compute something over a large set of data without revealing their individual inputs, furnishing enhanced privacy, and a means to produce a specific outcome. Consequently, sMPC affords advantages over two existing modes of key management: multi-sig and hardware storage.

Hardware wallets and multi-sig are both complicated to use for mainstream users. Hardware storage is offline, and connecting it to online sources breeds security challenges. Conversely, multi-sig works to an extent, but services like Casa are out of the price range of most consumers and also out of their technical peripherals.

Hot wallets [i.e., online wallets] continually demonstrate their proclivity for being hacked, and while they offer the best UX, they are major security vulnerabilities — once again highlighting the quandary of balancing security and UX.

With sMPC, security is bolstered by the fact that no single entity controls the key, and UX is improved because there can even be “keyless” services using sMPC. The perfect crypto wallet does not exist, but sMPC may come to redefine that narrative.

Outside of wallets, the market for sMPC solutions for enterprises is enormous, and an area where ArpaChain is looking to make an impact.

“The ARPA project aims to provide businesses and individuals with private computing power and secure data flow solutions,” says Xu. “The entry point of ARPA is enterprise-level privacy data sharing.”

ArpaChain to The Rescue

Requiring developers to consistently worry about security vulnerabilities takes away from their ability to focus on improving UX and other aspects of blockchain-based applications. Similarly, continually encrypting and decrypting data creates high technical barriers, something which sMPC diminishes.

But some of the real magic also derives from the ability of sMPC to remain secure even in a hostile environment.

Xu stated,

“We have implemented an agreement to support the participation of any party, and as long as there is an honest node in it, it can ensure the security of the data. Either of these two points is a breakthrough, and as far as we know, the vast majority of projects can only support the involvement of two parties.”

This is a powerful feature. No longer do parties need to independently hold keys that serve as singular attack vectors. With such security assurances on the back-end, a better UX can be transferred to the front-end — such as “keyless” wallets — which are already happening.

Providing users with an experience that does not require key management is a compelling step forward for the industry. Add in the ability of exchanges and other financial entities to securely, and privately, compute functions over large shared data sets [i.e., blockchains], and sMPC just might live up to its impressive reputation.

Xu mentioned,

“Imagine multi-party joint credit information, data leasing, secure data analysis, and other scenarios in the financial industry such as multi-source data joint risk control in the insurance industry with sMPC. In the future, applications will exist for corporate finance, marketing, medical applications, and even artificial intelligence.”

ArpaChain achieves this dynamic balance using an off-chain, layer two structure — making ARPA compatible with any public blockchain.

Xu said,

“The ARPA secure computing network can be used as a second layer to provide privacy computing capabilities for any public blockchain, enabling developers to build efficient, secure computing networks on ARPA computing networks, while also protecting the data privacy of business applications. Enterprise and personal data can be safely analyzed or utilized on ARPA computing networks without worrying about exposing data to any third party.”

A confluence of security, privacy, and better UX — a compelling proposition.

Overall, sMPC effectively removes the requirement of trusted third parties for security [i.e., custody], the cold/hardware storage solutions preferred by exchanges, and affords a better UX by removing significant points of friction altogether like key management.

What’s the cherry on top? Better privacy.

For enterprises, mainstream users, and the broader trajectory of crypto adoption alike, that’s a potent recipe for success.

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