By Mr. Roshan Aslam
When AI and cryptocurrencies made their first appearance, little was perceived by the global investor community over their long-term usage as financial tools. The initial school of thought regarding both technologies was far from favourable, but it has since witnessed a complete paradigm shift. Bitcoin is probably the world’s best-performing risk asset, especially during times of economic uncertainty. AI is witnessing constant development as part of its integration into numerous technologies, while Bitcoin is increasingly witnessing participation across levels — whales, institutions, retail and governments. However, as digital dependency rises in the crypto space, cyberattacks have led to constant setbacks — a critical aspect that is being bolstered by AI.
Cyberattacks in the crypto space are quickly becoming a recurring phenomenon. Exchanges & trading platforms, retail and institutional wallets are increasingly becoming victims of cyberattacks that are leading to significant financial loss. This is leading to concerns regarding Blockchain security, an aspect that is being considered critical to come up with a comprehensive solution. As per a report by a prominent blockchain analysis organisation, more than $3.8 billion and $1.7 billion worth of cryptocurrencies were stolen in 2022 and 2023 respectively and the subsequent call for adding an extra layer of security has led to the incorporation of Artificial Intelligence (AI) in the space. Social engineering, Phishing, ransomware and malware are the primary ways cyberattacks are targeting cryptocurrencies like Bitcoin. Integrating AI into critical systems offers a comprehensive solution to these challenges, with its considerable expertise in analysing huge volumes of data and identifying patterns.
Real-time threat identification
The most important aspect of enhancing Bitcoin’s cybersecurity is identifying real-time threat detection. With the help of AI, it is becoming increasingly simpler to analyse huge blocks of data to predict real-time threat detection. By mitigating the usage of manual inspection, it is possible to safeguard the blockchain network from unforeseen threats. This task is completed by looking for deviations and suspicious activities that may resemble a cyberattack.
This comprehensive effort is completed by AI’s Machine Learning algorithms that can analyse activities on the network. In case of suspicious activities, the AI system generates a warning for the security team or owners in real time — mitigating the risk and enhancing the overall security of the blockchain network.
Predictive modelling
AI models are trained with historical data and analysis to create a baseline for cybersecurity. This aspect helps AI systems to predict potential threats and malicious attempts, helping security teams to take appropriate measures to safeguard the network. In simpler terms, this predictive modelling helps AI to detect previously unforeseen patterns or traffic originating from certain IP addresses, which in turn gives a clearer idea to security teams to create a robust barrier.
Automation
One of the most innovative aspects of AI is to automate processes, which can be leveraged by Bitcoin stakeholders to detect fraud. The distinguishable factor in Bitcoin is that it is not regulated by any authorities, making it impossible for comprehensive monitoring of the space. This decentralised feature however can be integrated with AI-driven fraud detection systems to automate this process. As a result of this, the private networks of exchanges or trading platforms can be fed predetermined benchmarks for fraudulent activities, such as from blocked IPs or from hackers, reduce and mitigate the scope of account spoofing, accessing wallets and more.
Furthermore, this automation process can also be highly relevant in freezing certain transactions, locking particular wallets or reporting to relevant authorities for future evaluation. This feature can potentially save thousands of man-hours while enhancing the first response systems in cases of fraud or cyberattacks.
Safeguarding from common cyberattacks
One of the major aspects where AI is enhancing the cybersecurity aspect of Bitcoin is through safeguarding retail investors with authentication measures. While multi-factor authentication is used widely as the benchmark security measure, AI-driven behavioural biometrics can further supplement this comprehensive process. This particular aspect helps to distinguish users by benchmarking the way they tend to use their device, typing classifications and how the device is held. If AI algorithms detect user behaviour that is not similar to the owner of the device or the wallet, can deny accessibility or require confirmation that the user is the owner.
The growing emphasis on AI is leading to the integration of this new-age technology with other contemporary technologies. However, absolute integration of AI in blockchain networks to offer a comprehensive coverage of all exchanges, retail and institutional wallets will require more research and development in the space. Ethical and business considerations will also need to be made, considering it will be large volumes of user financial data under one single watchdog. However, developments in the space so far look promising while stakeholders are also receptive to the idea.
(The author is Mr. Roshan Aslam, Co-founder & CEO of GoSats, and the views expressed in this article are his own)
