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Bio-Inspired Agent-Based Architecture for Fraud Detection

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Published:21 September 2020Publication History

ABSTRACT

The information accessible on the Internet has been drastically increased over the last years. This information is not always produced by trusted sources. This fact leads to the emergence of fraudulent websites containing unappropriated information or having malicious intentions. The analysis of this large amount of information to detect possible fraud situations tends to be a very demanding task for human experts. Thus, it becomes a key issue to automatise these operations. This paper presents a Multi-Agent System (MAS) model and its implementation focused on automatically detecting fraudulent websites. The INGENIAS methodology and the MESA framework have been selected for this purpose. The system consists of a bio-inspired agent-based architecture based on insect colonies. Several basic agents carry out simple and distributed operations, while there is just one agent which aggregates the individual outcomes to obtain the final result. Some websites have been selected to illustrate the viability of the proposal.

References

  1. K. Jacobsen, "Time to put the internet in perspective," College & research libraries news, vol. 56, no. 3, pp. 144--147, 2019.Google ScholarGoogle Scholar
  2. D. R. Radev, J. Otterbacher, A. Winkel, and S. Blair-Goldensohn, "Newsinessence: summarizing online news topics," Communications of the ACM, vol. 48, no. 10, 2005.Google ScholarGoogle Scholar
  3. G. O. Bruen, WHOIS Running the Internet: Protocol, Policy, and Privacy. John Wiley & Sons, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  4. W. Seltzer, "Lumen database," https://lumendatabase.org/, 2019, [Online: accessed 25-Aug-2019].Google ScholarGoogle Scholar
  5. J. Ferber and G. Weiss, Multi-agent systems: an introduction to distributed artificial intelligence. Addison-Wesley Reading, 1999, vol. 1.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. J. Pavon, J. J. G′omez-Sanz, and R. Fuentes, "The INGENIAS method-′ ology and tools," Agent-Oriented Methodologies, vol. 9, pp. 236--276, 2005.Google ScholarGoogle ScholarCross RefCross Ref
  7. D. Masad and J. Kazil, "Mesa: an agent-based modeling framework," in 14th PYTHON in Science Conference, 2015, pp. 53--60.Google ScholarGoogle Scholar
  8. A. Garro, M. Muhlh¨ auser, A. Tundis, S. Mariani, A. Omicini, and¨ G. Vizzari, "Intelligent agents and environment," Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, p. 309, 2018.Google ScholarGoogle Scholar
  9. M. Pipattanasomporn, H. Feroze, and S. Rahman, "Multi-agent systems in a distributed smart grid: Design and implementation," in Power Systems Conference and Exposition, 2009. PSCE'09. IEEE/PES. IEEE, 2009, pp. 1--8.Google ScholarGoogle Scholar
  10. S. F. Railsback and V. Grimm, Agent-based and individual-based modeling: a practical introduction. Princeton university press, 2019.Google ScholarGoogle Scholar
  11. A. Fernandez-Isabel and R. Fuentes-Fern′ andez, "An agent-based plat-′ form for traffic simulation," in Soft Computing Models in Industrial and Environmental Applications, 6th International Conference SOCO 2011.Springer, 2011, pp. 505--514.Google ScholarGoogle Scholar
  12. C. Conati and M. Klawe, "Socially intelligent agents in educational games," in Socially Intelligent Agents. Springer, 2002, pp. 213--220.Google ScholarGoogle Scholar
  13. F. L. Bellifemine, G. Caire, and D. Greenwood, Developing multi-agent systems with JADE. John Wiley & Sons, 2007, vol. 7.Google ScholarGoogle ScholarCross RefCross Ref
  14. D. Helbing, "Agent-based modeling," in Social self-organization. Springer, 2012, pp. 25--70.Google ScholarGoogle Scholar
  15. C. M. Macal and M. J. North, "Agent-based modeling and simulation," in Proceedings of the 2009 Winter Simulation Conference (WSC). IEEE, 2009, pp. 86--98.Google ScholarGoogle Scholar
  16. B. Henderson-Sellers and P. Giorgini, Eds., Agent-Oriented Methodologies. IGI Global, 2005.Google ScholarGoogle ScholarCross RefCross Ref
  17. P. Bresciani, A. Perini, P. Giorgini, F. Giunchiglia, and J. Mylopoulos, "Tropos: An agent-oriented software development methodology," Autonomous Agents and Multi-Agent Systems, vol. 8, no. 3, pp. 203--236, 2004.Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. A. E. Hassanien and E. Emary, Swarm intelligence: principles, advances, and applications. CRC Press, 2018.Google ScholarGoogle ScholarCross RefCross Ref
  19. O. Deepa and A. Senthilkumar, "Swarm intelligence from natural to artificial systems: Ant colony optimization," Networks (Graph-Hoc), vol. 8, no. 1, pp. 9--17, 2016.Google ScholarGoogle Scholar
  20. J. Alcock and D. R. Rubenstein, Animal behavior. Sinauer Associates Sunderland, MA, USA, 2019.Google ScholarGoogle Scholar
  21. D. M. Gordon, "From division of labor to the collective behavior of social insects," Behavioral ecology and sociobiology, vol. 70, no. 7, pp. 1101--1108, 2016.Google ScholarGoogle Scholar
  22. M. Olaifa, T. Mapayi, and R. Van Der Merwe, "Multi ant la: An adaptive multi agent resource discovery for peer to peer grid systems," in 2015 Science and Information Conference (SAI). IEEE, 2015, pp. 447--451.Google ScholarGoogle Scholar
  23. M. Dorigo, E. Bonabeau, and G. Theraulaz, "Ant algorithms and stigmergy," Future Generation Computer Systems, vol. 16, no. 8, pp. 851--871, 2000.Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. D. C. Schmidt, "Model-driven engineering," IEEE Computer Society, vol. 39, no. 2, p. 25, 2006.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. A. G. Kleppe, J. B. Warmer, and W. Bast, MDA Explained: The Model Driven Architecture: Practice and Promise. Addison-Wesley Professional, 2003.Google ScholarGoogle ScholarDigital LibraryDigital Library

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      cover image ACM Other conferences
      IMMS '20: Proceedings of the 3rd International Conference on Information Management and Management Science
      August 2020
      120 pages
      ISBN:9781450375467
      DOI:10.1145/3416028

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      Publication History

      • Published: 21 September 2020

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