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Home Crypto News & Analysis On-Chain Data & Metrics

Improving Web3.0 Security Through On-Chain Data Analytics: Insights from Industry Leaders – Digital Transformation News

by Dr. Jane Chen
January 23, 2024
in On-Chain Data & Metrics
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Improving Web3.0 Security Through On-Chain Data Analytics: Insights from Industry Leaders – Digital Transformation News
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By Jenny Zheng

On 28 September 2023, a panel of experts gathered at the Singapore Management University (SMU) to delve into the areas of on-chain data and Web3 security. Prof. Feida Zhu, a well-known figure in information systems and co-director of the SMU Blockchain Lab, took the reins as the moderator. The panel featured luminaries including Aby Huang, the CEO of SlowMist, a prominent blockchain security firm; Neal, CEO of BugRap, a decentralized bug bounty platform; Anndy Lian, an advisor at Bybit, a global cryptocurrency exchange; and Xiaolin Wen, a research scientist at SMU.

The panelists explored a range of topics, starting with the role of on-chain data analysis in strengthening blockchain network security. They shared their perspectives on the potential of on-chain data analytics to improve security measures, detect fraudulent activity, identify vulnerabilities and effectively communicate findings.

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 analysis can evaluate the security of smart contracts, tokens, dApps and protocols by considering factors such as code quality, audit results, governance mechanisms and community trust.

Neal echoed Aby’s sentiments, underscoring how on-chain data analytics promotes transparency and accountability. He explained its role in verifying the correctness and integrity of smart contracts and transactions through cryptographic evidence and consensus mechanisms. Neal also noted that economic models and game theory can be used to incentivize positive behavior while discouraging malicious behavior.

Anndy Lian emphasized the importance of feedback and improvement in improving 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. In addition, he discussed the potential of identifying pain points and bottlenecks in these networks using benchmarks and comparative analysis.

Xiaolin Wen concluded that on-chain data analysis contributes intelligence and innovation to blockchain security. He highlighted its ability to uncover new patterns and insights through advanced techniques such as machine learning, natural language processing and graph analysis. Furthermore, he discussed 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

The panelists also shared examples of how on-chain data analytics can facilitate the early detection of fraud and the 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 such as the Mixin incident involving $200 million worth of crypto assets. Anndy Lian emphasized the role of education in promoting security awareness among crypto users, and highlighted the importance of platforms such as SlowMist that offer free live monitoring to prevent financial losses.

Prof. Feida Zhu offered insights into the future of Web3 security. He predicted that advances in on-chain analytics will lead to proactive security measures, adapt to changing circumstances and promote collaboration between stakeholders. Web3 security, he claimed, would shift from a reactive, static and isolated model to one that is proactive, adaptive and collaborative.

Closure

The panelists agreed that on-chain data analytics hold unparalleled promise for discovering transaction intent within the blockchain’s rich data tapestry. Techniques such as graph analysis, network analysis, community detection, and link prediction can illuminate the dynamics of transaction networks. Furthermore, methodologies such as game theory, behavioral economics, social psychology and decision theory can provide insights into the strategies, preferences and emotions of transaction participants.

This event was organized by Moledao in conjunction with an MOU signing between SMU and SlowMist, illustrating the collaborative spirit of the blockchain community to advance Web3 security.

The author is a blockchain specialist

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Disclaimer for Uncirculars, with a Touch of Personality:

While we love diving into the exciting world of crypto here at Uncirculars, remember that this post, and all our content, is purely for your information and exploration. Think of it as your crypto compass, pointing you in the right direction to do your own research and make informed decisions.

No legal, tax, investment, or financial advice should be inferred from these pixels. We’re not fortune tellers or stockbrokers, just passionate crypto enthusiasts sharing our knowledge.

And just like that rollercoaster ride in your favorite DeFi protocol, past performance isn’t a guarantee of future thrills. The value of crypto assets can be as unpredictable as a moon landing, so buckle up and do your due diligence before taking the plunge.

Ultimately, any crypto adventure you embark on is yours alone. We’re just happy to be your crypto companion, cheering you on from the sidelines (and maybe sharing some snacks along the way). So research, explore, and remember, with a little knowledge and a lot of curiosity, you can navigate the crypto cosmos like a pro!

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Dr. Jane Chen

Dr. Jane Chen

Armed with a PhD in cryptography and years of research, Dr. Chen dives deep into the technical intricacies of blockchain. Her insightful analyses of white papers and on-chain data provide a unique understanding of the technology's potential and limitations.

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