Layer-2 Networks Integrate AI to Boost Scalability, Security, and Efficiency

Layer-2 (L2) networks are gaining momentum, yet it remains uncertain which specific solutions will achieve widespread adoption. While it is too early to make definitive predictions, several L2s have begun incorporating artificial intelligence (AI) to enhance scalability, security, and operational efficiency.

This development aligns with broader market trends. Recent insights indicate that the intersection of AI and blockchain technology is projected to be worth over $2.7 billion by 2031.Why L2s Are Incorporating AI

Although the convergence of blockchain and AI is still evolving, these technologies have the potential to refine crypto trading strategies, improve smart contract development, and strengthen security protocols.

Karan Bharadwaj, Founder and CEO of Layer-2 network Arithmic, told Cryptonews that AI can optimize transaction throughput by improving the speed of proof generation and verification. He noted that AI solutions can also manage network congestion through intelligent resource allocation, ensuring smooth performance even during periods of high demand.

This capability is crucial, as L2 networks are designed to increase scalability by offloading numerous transactions from the main blockchain to a secondary layer.

AI Used to Detect and Prevent Malicious Transactions

Bharadwaj also highlighted that AI enhances security by identifying anomalies and potential threats before they affect the L2 network.

This approach is already being implemented. Jan Gorzny, Co-founder of Zircuit, told Cryptonews that Zircuit, a zero-knowledge rollup solution, leverages AI for sequencer security.

“This security feature within our rollup means that our AI-based sequencer monitors the mempool – which is the node’s collection of all unconfirmed transactions it has seen – for malicious transactions to prevent their inclusion in a block,” Gorzny explained.

Read the report from @dl_research to learn how we’re protecting both users and protocols from smart contract exploits while being the major liquidity hub for all LST and LRT assets https://t.co/YeCHcYYQV2

— Zircuit (@ZircuitL2) August 15, 2024

According to Gorzny, the goal of AI-enabled sequencer-level security is to create a safer L2 environment that protects decentralized applications (dApps) and their users from hacks and malicious actors.

“When other L2s are hacked, they have to resort to measures like block reversion or hard forks to secure the chain,” she said. “Zircuit aims to prevent exploits from happening in the first place.”

Gorzny explained that Zircuit uses an AI system to inspect and simulate transactions as they are considered for inclusion on the network.

“The AI determines whether a transaction is malicious by considering the outcomes of the transaction in the context of the current blockchain network,” Gorzny mentioned. “When the AI assesses a transaction for malicious behavior, it examines unusual activity within the blockchain.”

For instance, Gorzny noted that if a transaction withdraws liquidity in large volumes without proper collateral, it may signal a hack. She added that Zircuit’s AI is trained to recognize such patterns, flagging them as potentially malicious based on historical data and known attack strategies.

Gorzny shared that Zircuit’s system has been trained on over 4.8 billion transactions across more than 20 blockchain networks.

AI Used for Smart Contract Audits and Security

The Numerico L2 blockchain is also integrating AI to bolster network security. A Numerico spokesperson told Cryptonews that the Numerico ecosystem recently implemented an “AI smart contract audit system.”

“This feature performs audits to identify bugs or vulnerabilities in smart contract code,” the spokesperson said.

They added that AI can analyze vast amounts of data in real-time to optimize network performance and security beyond current capabilities.

“By leveraging AI, blockchain networks gain a competitive edge that will be hard or impossible to compete with,” the spokesperson remarked.

Other AI Use Cases for Layer-2 Solutions

While AI is well-suited for enhancing L2 security, Bharadwaj pointed out that these tools can also refine user experiences through personalized interactions and automation.

“This makes the technology more intuitive and accessible,” he said.

For example, Numerico offers a tool called “Calculus AI” that creates personalized trading strategies for users. A Numerico spokesperson mentioned that an AI development tool allows users with minimal Solidity knowledge to deploy on-chain products and projects across the Numerico ecosystem.

Additionally, it has been reported that Ethernity – a platform offering licensed non-fungible tokens (NFTs) featuring celebrities – will use AI for its Layer-2 solution.

The Ethernity Chain Layer-2 solution will utilize AI to implement Digital Rights Management (DRM) controls. This aims to prevent counterfeit trading while protecting creators’ intellectual property.

Challenges Combining AI and Blockchain

While using AI to enhance blockchain efficiencies is logical, several challenges may arise.

Gorzny noted that performance and accuracy are primary challenges. However, she mentioned that Zircuit has a strong engineering team dedicated to resolving these issues.

“Zircuit’s AI can keep up with the network’s blazingly fast 2-second block time, while also maintaining a false positive rate as low as 0.01%,” Gorzny said.

According to Numerico, one of the biggest challenges in integrating AI with an L2 network is ensuring that algorithms can handle the scalability demands and security requirements of blockchain technology.

“Additionally, maintaining low latency while processing large amounts of data in real time is critical,” the spokesperson said. “These challenges can be addressed by optimizing AI models specifically for blockchain use, leveraging advanced L2 scaling solutions, and continuously updating the AI to adapt to new threats and network changes.”

L2s Will Use AI Moving Forward

Despite these challenges, Gorzny believes that using AI is more efficient than other approaches, such as formal proofs of correctness.

“Using our AI-based system, we can evaluate a particular transaction with a particular context, in order to determine if the transaction is malicious. This is a lot easier than trying to prove that there is never going to be a malicious transaction that can exploit a particular smart contract,” she said.

Given these benefits and others, Bharadwaj believes that more L2s will increasingly adopt AI in the future.

“It will allow them to optimize scalability and enhance security, while simultaneously enhancing user experience,” he said.

In turn, Bharadwaj mentioned that this will lower the barrier to entry and broaden accessibility.

He added that while it is interesting to observe L2s utilizing AI, an equally important question is: “how can AI utilize Layer-2s?”

“I think Layer-2 solutions can be potentially used in the future to scale up and decentralize AI networks to meet their heavy computational requirements,” Bharadwaj commented.

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