2nd Transparency, Regulation, and Analytics in Crypto-Asset Ecosystems workshop (TRACE)

Crypto-asset analytics plays a central role in ensuring trust, security, and regulatory  compliance within increasingly complex decentralized ecosystems. While blockchain systems  provide inherent transparency, the scale, heterogeneity, and cross-chain nature of transaction  data – combined with the need to integrate off-chain information sources – often obscure  actionable insights, necessitating advanced and interdisciplinary analytical frameworks. 

The second edition of the TRACE (Transparency, Regulation, and Analytics in Crypto-Asset Ecosystems) workshop addresses key challenges at the intersection of blockchain forensics,  compliance analytics, machine learning, economics, and law and regulation, with a particular  focus on detecting financial crime – including money laundering, crypto scams, and fraud – and enabling reliable entity attribution and risk analysis across blockchain-based systems. 

Core topics include on-chain (including cross-chain) data processing, graph- and network based transaction analysis, integration of off-chain intelligence to support attribution and risk  assessment. The workshop further explores machine learning approaches for anomaly  detection, RegTech solutions, DeFi attack vectors, smart contract security, and governance  analytics. Contributions may also lie in the development of policy recommendations.  

Aligned with BRAINS 2026’s mission, the second edition of the TRACE workshop provides a  platform for interdisciplinary exchange, bridging academia, industry, and policymakers to 

advance tools and frameworks for secure and trustworthy crypto-asset oversight. The program will feature peer-reviewed research, case studies, as well as two keynotes on (1) emerging  trends in analytics and (2) the evolution of regulatory and compliance frameworks. 

Topics

Topics of interest include, but are not limited to: 

Blockchain forensics and data analytics 

• Large-scale on-chain data processing: Handling high-volume, distributed ledger data to  uncover hidden patterns and relationships. 
• Graph & network analysis: Applying graph-based techniques for transaction clustering,  address attribution, and detection of complex network structures. 
• Data management & integration: Approaches for integrating off-chain data, managing  metadata, and ensuring data consistency across multiple ledgers. 
• Incident response & forensic analytics: Frameworks and case studies for post-incident  investigation, digital evidence gathering, and attribution of malicious events. 

Compliance analytics and fraud detection 

• Machine learning & anomaly detection: Employing supervised/unsupervised models to  identify malicious actors, ransomware payments, and other illicit activities.
•  RegTech & automated monitoring: Tools and platforms for compliance monitoring,  AML/KYC checks, and real-time risk assessment. 
• Automated threat monitoring: Early warning systems that continuously track suspicious  behavior or address movements on-chain. 
• Privacy-preserving compliance: Approaches (e.g., zero-knowledge proofs) that enable  regulatory checks without compromising user confidentiality. 

Regulatory-enforcement support systems and policy recommendations

• Policy recommendations & legal frameworks: Analyses that inform regulators on  evolving risks and best practices for enforcing crypto-asset regulations. 
• Cross-border oversight: Solutions addressing overlapping or conflicting jurisdictions and  enabling international cooperation in crypto-asset investigations. 

Decentralized finance (DeFi) analytics 

• Attack vectors & risk modeling: Identifying vulnerabilities and quantifying liquidity,  market, and credit risks in DeFi protocols. 
• Governance & voting mechanisms: Evaluating stakeholder participation, incentive  structures, and proposal outcomes in decentralized governance.
• Smart contract security & formal verification: Tools and methodologies to ensure  correct, fraud-resistant code execution in DeFi ecosystems. 
• Liquidity & collateral insights: Monitoring metrics like impermanent loss, liquidation  thresholds, and overall protocol stability. 

Interoperability & cross-chain analysis 

• Cross-chain protocols & bridges: Investigating trustless bridging technologies,  communication protocols, and data synchronization across multiple ledgers.
• Multi-ledger risk management: Techniques to detect fraud, laundering, or double  spending when assets move between different blockchain networks. 
• Data consistency & redundancy: Approaches for ensuring reliable transaction records,  state proofs, and consensus across diverse ecosystems. 
• Standards & frameworks: Comparative studies of emerging industry standards to  facilitate seamless interoperability. 

---

Submission Guidelines

Submissions are invited on novel methods, tools, and case studies in crypto-asset analytics.  Interdisciplinary work combining technical insights with regulatory or economic dimensions is  especially encouraged. Both theoretical contributions and applied research will be considered. 

Papers submitted to TRACE 2026 Workshop will be assessed based on originality, technical soundness, clarity and interest to a wide audience. All submissions must be written in English and must use standard IEEE two-column conference template, available for download from the IEEE website: https://www.ieee.org/conferences/publishing/templates.html

Workshop papers can between 4 – 8 pages , including tables, figures and references.

Only PDF files will be accepted for the review process and all submissions must be done electronically through EDAS at: https://edas.info/N35434

---

Importante deadlines

• Workshop paper submission deadline: 15 July 2026
• Acceptance notification: 1 September 2026
• Camera-ready paper submission: 15 September 2026
• TRACE 2026 Workshop date: 13 October 2026

---

Workshop Chairs