By Jenny Zheng
On September 28, 2023, a group of experts gathered at the Singapore Management University (SMU) to delve into the field of blockchain data and Web3 security. Professor Feida Zhu, renowned information systems personality and co-director of the SMU Blockchain Lab, took the reins as moderator. The panel included luminaries including Aby Huang, CEO of SlowMist, a leading blockchain security company; Neal, CEO of BugRap, a decentralized bug bounty platform; Anndy Lian, advisor at Bybit, a global company cryptocurrency
Panelists explored a range of topics, starting with the role of on-chain data analytics in strengthening the security of blockchain networks. They shared their views on the potential of on-chain data analytics to improve security measures, detect fraudulent activity, identify vulnerabilities, and effectively communicate results.
Improving Blockchain Network Security
Aby Huang highlighted the real-time benefits of on-chain data analytics to improve security. He discussed its ability to monitor blockchain networks, assess risks, and detect anomalies, such as irregular transactions or suspicious contract calls. Furthermore, he highlighted how on-chain data analytics can assess the security of smart contracts, tokens, dApps and protocols by considering factors such as code quality, audit results, mechanisms governance and community trust.
Neal echoed Aby’s sentiments, emphasizing how on-chain data analytics promotes transparency and accountability. He explained his role in verifying the correctness and integrity of smart contracts and transactions through cryptographic proofs and consensus mechanisms. Neal also noted that economic models and game theory can be leveraged to encourage positive behavior while discouraging malicious actions.
Anndy Lian emphasized the importance of feedback and improvement in strengthening security measures. He illustrated how on-chain data analytics measures the performance and efficiency of blockchain networks using key metrics such as throughput, latency, scalability, and cost. Additionally, it discussed its ability to identify weaknesses and bottlenecks in these networks using benchmarking and benchmarking.
Xiaolin Wen concluded that on-chain data analysis brings intelligence and innovation to blockchain security. He highlighted its ability to discover new patterns and insights through advanced techniques such as machine learning, natural language processing and graph analysis. Furthermore, he explained how interdisciplinary approaches, such as cryptography, software engineering and human-computer interaction, enable the development of new solutions and applications for blockchain security.
Early detection of fraud and security breaches
Panelists also shared examples of how on-chain data analytics can facilitate early detection of fraud and prevention of security breaches in the blockchain space. Aby Huang described how SlowMist actively monitors and investigates hacking incidents in the blockchain ecosystem, including recent cases like the Mixin incident involving $200 million in crypto assets. Anndy Lian highlighted the role of education in raising security awareness among crypto users, emphasizing the importance of platforms like SlowMist offering free live monitoring to avoid financial losses.
Professor Feida Zhu offered insight into the future of Web3 security. He predicted that advances in on-chain analytics would lead to proactive security measures, adapting to changing conditions and fostering collaboration among stakeholders. Web3 security, he said, would move from a reactive, static and isolated model to a proactive, adaptive and collaborative model.
Conclusion
Panelists agreed that on-chain data analysis holds unprecedented promise for uncovering transaction intentions within blockchain’s rich tapestry of data. Techniques such as graph analysis, network analysis, community detection, and link prediction can shed light on the dynamics of transaction networks. Additionally, methodologies such as game theory, behavioral economics, social psychology, and decision theory can provide insight into the strategies, preferences, and emotions of transaction participants.
This event was organized by Moledao in conjunction with the signing of a Memorandum of Understanding between SMU and SlowMist, exemplifying the collaborative spirit of the blockchain community to advance Web3 security.
The author is a blockchain specialist
