cff-version: 1.2.0
message: "If you use MIESC in your research, please cite it as follows."
title: "MIESC: Multi-layer Intelligent Evaluation for Smart Contracts"
version: 3.0.0
date-released: "2025-01-01"
authors:
  - family-names: Boiero
    given-names: Fernando
    email: fboiero@frvm.utn.edu.ar
    affiliation: "Universidad de la Defensa Nacional (UNDEF) - IUA Córdoba"
repository-code: "https://github.com/fboiero/MIESC"
url: "https://github.com/fboiero/MIESC"
abstract: >
  MIESC is an automated security assessment framework for Ethereum smart contracts
  that integrates 15 specialized security tools with AI-powered correlation and
  compliance mapping. Built as a Model Context Protocol (MCP) agent, MIESC enables
  collaborative cyberdefense through inter-agent communication. The framework
  implements defense-in-depth principles and provides comprehensive vulnerability
  detection with 89.47% precision, 86.2% recall, and Cohen's Kappa of 0.847
  (validated on 5,127 contracts). MIESC maps findings to 12 international security
  standards including ISO/IEC 27001:2022, NIST CSF, OWASP SC Top 10, CWE, SWC,
  and MITRE ATT&CK.
keywords:
  - smart contracts
  - blockchain security
  - vulnerability detection
  - cyberdefense
  - multi-agent systems
  - Model Context Protocol
  - automated security assessment
  - defense-in-depth
  - ISO 27001
  - NIST CSF
license: GPL-3.0-or-later
preferred-citation:
  type: thesis
  title: >
    Integrated Security Assessment Framework for Smart Contracts: A
    Defense-in-Depth Approach to Cyberdefense
  authors:
    - family-names: Boiero
      given-names: Fernando
  institution:
    name: "Universidad de la Defensa Nacional (UNDEF) - IUA Córdoba"
  thesis-type: "Master's Thesis"
  department: "Cyberdefense"
  year: 2025
  abstract: >
    This thesis presents MIESC, a comprehensive security assessment framework for
    smart contracts based on defense-in-depth principles. The work addresses the
    critical challenge of false positives in automated security analysis through
    multi-tool integration and AI-powered correlation. Key contributions include:
    (1) Novel MCP-based multi-agent architecture for collaborative cyberdefense,
    (2) Empirical validation on 5,127 real-world contracts demonstrating 34%
    improvement over single-tool analysis, (3) Automated compliance mapping to 12
    international standards, (4) Open-source implementation enabling reproducible
    security research. The framework achieved 89.47% precision, 86.2% recall, and
    Cohen's Kappa of 0.847, representing strong agreement with expert auditors.
    Scientific validation followed rigorous experimental methodology with controlled
    datasets and statistical analysis.
references:
  - type: article
    title: "Empirical Review of Automated Analysis Tools on 47,587 Ethereum Smart Contracts"
    authors:
      - family-names: Durieux
        given-names: Thomas
      - family-names: Ferreira
        given-names: João F.
      - family-names: Abreu
        given-names: Rui
      - family-names: Cruz
        given-names: Pedro
    year: 2020
    journal: "ACM/IEEE International Conference on Software Engineering (ICSE)"
  - type: article
    title: "The Protection of Information in Computer Systems"
    authors:
      - family-names: Saltzer
        given-names: Jerome H.
      - family-names: Schroeder
        given-names: Michael D.
    year: 1975
    journal: "Proceedings of the IEEE"
    volume: 63
    issue: 9
  - type: article
    title: "Intelligent Agents: Theory and Practice"
    authors:
      - family-names: Wooldridge
        given-names: Michael
      - family-names: Jennings
        given-names: Nicholas R.
    year: 1995
    journal: "The Knowledge Engineering Review"
    volume: 10
    issue: 2
  - type: generic
    title: "Model Context Protocol Specification"
    authors:
      - name: "Anthropic"
    year: 2024
    url: "https://modelcontextprotocol.io"
