AI Applications Explained: Network Consensus
Blockchain technology creates global, immutable repositories that guarantee information non-repudiation and accountability. Through community consensus, decentralized blockchain technology, the system records information that makes it hard or almost impossible to change, hack, or cheat the system. Furthermore, the growth in the quantity and availability of data on computer networks makes processing and managing massive amounts of data with ever-lower latencies difficult.
As a result, artificial intelligence and machine learning techniques increase significantly, allowing them to become enablers for next-generation networks. This article is dedicated to these emerging technologies that are reshaping the world by enabling new distributed and knowledge-driven security applications and services while enabling more dependable computer networks.
Take, for example, the paper of Vanessa Chicarino focusing on “On the Detection of Selfish Mining and Stalker Attacks in Blockchain Networks.” She ponders that bifurcations or forks naturally arise in the blockchain until it reaches a consensus. On the other hand, malicious users may force forks to occur to profit from network incentives or stifle a single user’s revenue. The paper identifies two key harmful behaviours, selfish mining and stalking, and presents methods for detecting attacks based on blockchain height. According to simulation data, the proposed heuristics are accurate in determining that the blockchain network is under attack. Thus, a task AI can easily adopt.
Next, a paper by Samuel Masseport called “Proof of Usage: User-centric consensus for data provision and exchange.” In it, the author introduces a new consensus protocol for permission blockchain networks. Users are encouraged to spend coins in the network to have a chance to mine the next block of the chain under the proposed protocol. The proof-of-usage protocol is an alternative to the proof-of-work protocol, and it is based on the same ideas as proof-of-stake and proof-of-activity. Thus, in this protocol, blockchain and AI work together to assure network security.
Finally, a paper from Gabriel Reis Carrara and his colleagues entitled “Consistency, Availability and Partition Tolerance in Blockchain: A Survey on the Consensus Mechanism over Peer-to-Peer Networking” illustrates some of the issues AI could solve. First, the authors note that blockchain, as any distributed system, is subjected to the CAP theorem (Consistency, Availability, and Partition Tolerance). Thus, any consensus mechanism on blockchain assures at most two out of the three properties despite one of them. Second, the paper shows the drawbacks and costs of each consensus mechanism to the blockchain network. Drawbacks such as speed, cost, and double-checking of information, which AI can offer solutions to.
According to Raj Shroff from The Startup, Artificial Intelligence solutions will soon run on top of blockchains, increasing machine learning capability and creating new financial products.
Because both blockchain and AI can affect and enact data in distinct ways, combining them makes sense and potentially push data exploitation to new heights. Simultaneously, incorporating machine learning and AI into the blockchain and vice versa can improve blockchain’s fundamental architecture while also enhancing AI’s capabilities. Furthermore, blockchain can make AI clearer and more accessible, allowing us to track and understand why machine learning decisions are made. The blockchain and its ledger can track all the data and variables that go into a machine learning decision.
Furthermore, AI can improve blockchain efficiency significantly more effectively than people or even traditional computing. A glance at how blockchains are currently performed on normal computers demonstrates this, with a significant amount of computing power required to complete even basic functions.
VAIOT’s AI Function
While VAIOT’s AI is not directly involved in the network’s consensus, the AI plays a significant role in the project. Artificial Intelligence is included in every aspect of the VAIOT Platform, allowing for full interoperability, safeguarding the platform with AI-driven security procedures, and transforming VAIOT’s digital contracts into intelligent contracts. Within the VAIOT project, AI serves to:
- Simplify the process of creating Intelligent Contracts (via the Virtual Intelligent Assistant).
- Employ mechanisms to search, analyze and provide the user with the best possible solution and data in each situation.
- Propose a contract in line with the best practices on the legal and code level and fulfill the user’s requirements.
- Offer a comprehensive user experience to use additional services depending on the type of the contract.
- Prevent fraud within the VAIOT network.
- Self-diagnose the VAIOT network, including improved security mechanisms.