Ethereum Founder Vitalik Buterin Looks Forward to the Integration of AI and Cryptography: Building a Secure and Free Digital Future
With the rapid development of the digital world, trust and security have become crucial issues. In this context, organizations are constantly seeking innovative solutions to protect their systems and data from vulnerabilities and malicious activities. Vitalik Buterin, the founder of Ethereum, has expressed deep insights into the prospects, challenges, and security visions of AI and encryption technology.
Vitalik Buterin is optimistic about the combination of AI and encryption technology, believing that this combination will bring higher security and practicality. He specifically mentioned the challenges posed by AI as part of the game rules and emphasized the need for caution in this field to avoid unpredictable consequences and misuse. At the same time, Vitalik also expressed great interest in AI-assisted code verification and vulnerability discovery, seeing it as a key to addressing risks in technologies like Ethereum. He pointed out that AI can serve as an interface for understanding the crypto world and help users ensure their actions align with their intentions. For example, the fraud detection feature in MetaMask is an example of using AI to identify and prevent potential fraudulent behavior. However, he also highlighted the risks involved, noting that in cryptography, open-source is crucial for ensuring security, but the openness of AI may increase vulnerability to adversarial machine learning attacks. Therefore, he believes that purely AI interfaces may currently carry excessive risks, and combining AI with traditional interfaces may be a more viable direction.
As a leading technology company, AgentLayer has developed an advanced AI Agent called AegisAI to address these issues. This AI Agent is based on state-of-the-art large language models (LLMs) and introduces a unified evaluation framework called LLM4Vuln. This framework decouples the vulnerability reasoning capability of LLM from other functionalities, allowing organizations to gain deeper insights into potential vulnerabilities and take appropriate measures to mitigate them. Building upon the LLM4Vuln framework, AgentLayer’s AI Agent incorporates various functionalities such as knowledge augmentation, context supplementation, and customized alerting schemes. By integrating raw vulnerability reports and aggregated vulnerability knowledge, AegisAI can retrieve relevant vulnerability knowledge based on similarity, significantly improving vulnerability identification and accurate reasoning capabilities. Additionally, by leveraging the function invocation mechanism of LLM, AegisAI can obtain more contextual information about the target code to gain deeper understanding of potential vulnerabilities.
Furthermore, AgentLayer’s AI Agent adopts multiple different LLM models and customizes corresponding alerting schemes based on vulnerability analysis scenarios. These alerting schemes align and structure the analysis outputs of LLM, making the results more understandable and evaluable. Through rigorous testing, AgentLayer’s AegisAI has achieved significant results in smart contract vulnerability detection, uncovering critical findings regarding knowledge augmentation, context supplementation, and model variations. It has successfully identified multiple zero-day vulnerabilities, providing timely security protection for organizations.
In addition to AI, Vitalik also highly values zero-knowledge proof technology. He believes that this technology is crucial for protecting privacy and freedom of speech. With zero-knowledge proofs, people can prove their credibility without revealing specific identities, offering new possibilities for privacy protection. He also mentioned the importance of zero-knowledge proofs in applications such as public identity systems or online voting. Regarding the combination of AI and blockchain, Vitalik believes that this combination can bring higher security and practicality to AI applications. He specifically mentioned the concept of “AI participating in on-chain micro-market,” suggesting that it can create an open ecosystem continuously iterated and improved by dozens of individuals, effectively curbing adversarial attacks. He also emphasized the importance of hiding training data while ensuring the integrity of the training data creation process.
Additionally, Vitalik talked about the concept of AI as a game objective, where the goal is to build and maintain an AI that can be used for other purposes by designing blockchains, DAOs, and similar mechanisms. He considers this as a long-term and interesting field because it involves AI security and AI ethics. He mentioned some possible technologies, such as using blockchain and multi-party computation to create scalable decentralized private AI or employing cryptographic forms like zero-knowledge proofs to create AI with natural emergency stop switches.
In the aspect of combining AI and encryption technology, AgentLayer’s practices provide strong support for Vitalik’s theories. AgentLayer’s AegisAI combines the advantages of AI and encryption technology to provide organizations with a more comprehensive and intelligent vulnerability detection solution, ensuring a safer and more trustworthy digital world.
Regarding the frequent occurrence of deepfakes (AI-generated fake audio and video) in the cryptocurrency field and elsewhere, Vitalik also expressed his concerns. He believes that security measures against deepfakes should be a natural and non-awkward habit, and in addition to other protective layers, it is worth incorporating them into workflows. He suggests stacking multiple technologies together, such as pre-agreed passwords, consensus on coercion keys, protection against man-in-the-middle attacks, daily limits, and delays, to address this challenge.
In conclusion, Vitalik Buterin’s views on the combination of AI and encryption technology reflect his pursuit of openness, freedom, security, and practicality. He believes that by combining AI with advanced technologies like blockchain, wecan achieve higher security, privacy, and trust in the digital world. AgentLayer’s AegisAI is an example of an AI Agent that integrates AI and encryption technology to provide organizations with advanced vulnerability detection capabilities. With the right approach and cautious consideration of risks, the combination of AI and encryption technology holds great potential for enhancing security and privacy in various applications. However, it is important to remain vigilant and address the challenges and risks associated with AI and encryption to ensure the development of a safe and trustworthy digital ecosystem.
