AI has various applications in blockchain technology. It has the potential to enhance blockchain systems by analysing smart contracts, detecting fraud, optimising scalability, and enabling tokenisation, among other issues. But it also comes with challenges, for instance, in the form of AI-driven attacks aimed at exploiting blockchain vulnerabilities.
AI to complement blockchain technology
AI algorithms are already used to optimise the consensus mechanism used on cryptocurrency blockchains by analysing and enhancing the efficiency and effectiveness of the consensus protocols. Using machine learning algorithms and data analysis, AI can identify patterns, optimise parameters, and predict successful consensus strategies. Additionally, AI can help address challenges related to scalability and energy consumption.
AI can also enable the tokenisation of assets, facilitating the creation and management of digital assets on blockchain platforms. Asset management systems powered by AI can automate processes like asset valuation, portfolio management, and investment decision-making. Security issues associated with blockchain can be identified and mitigated using AI. For instance, AI is used to analyse patterns in DDoS attacks and identify possible security holes in the code. AI techniques are also employed to verify smart contracts and reduce the likelihood of exploits and vulnerabilities. Furthermore, by analysing transaction patterns and identifying suspicious behaviour, AI can detect fraudulent activities within blockchain networks and help prevent illicit activities such as fraud and money laundering. Additionally, AI can help enhance the privacy and security of blockchain networks by developing advanced encryption algorithms and employing privacy-preserving techniques to protect sensitive data and transactions.
As is the case with other technologies, different blockchain systems are often incompatible with each other. AI solutions that enable different blockchains to communicate are in development and will potentially create new opportunities.
Challenges at the intersection of AI and blockchain
The integration of AI and blockchain technology presents several challenges. Adversarial attacks are a significant concern, as AI can exploit blockchain system vulnerabilities and compromise security and integrity. The analytical capabilities of AI can potentially de-anonymise blockchain data, thereby raising privacy concerns. Additionally, the resource-intensive nature of AI systems often necessitates significant computational power; when integrated with blockchain systems, AI systems can exacerbate scalability and performance issues (i.e. the limited resources of blockchain networks may be strained by the processing power and storage requirements of AI tasks). Finally, governance and regulatory challenges arise when determining responsibility and accountability in decentralised AI-powered blockchain systems.
Digitalisation, e-commerce, and the emergence of e-money in our daily lives made the notion of non-physical currency quite common. Since the early 2000s, the idea of a digital payment system and a digital currency native to the Internet has become very attractive.
What is a blockchain? Simply put, it is a data ledger (think of an accounting ledger, which records every ‘in’ and ‘out’ transaction). The ledger is distributed, which means that many copies of the same ledger exist on computers worldwide. It is also protected by strong cryptography to protect it from malicious actors attempting to change any information within the Blockchain
