Skip to main content
Log in

A logical consideration on fraudulent email communication

  • Original Article
  • Published:
Artificial Life and Robotics Aims and scope Submit manuscript

Abstract

One of the most serious problems in modern society is that internet users are deceived by various fake information. In this paper, we analyse a scenario based on an actual incident of fraud called business email compromise (BEC). We suppose that each email, in the incident, step-wisely changes user’s thinking and makes him or her believe the emails. If fraud has such a step-by-step mechanism, it allows us to consider counter measures for dissuading a user from decision-making on the way. We discuss features and factors of the incident based on formulations of Channel theory. Our analysis revealed that each email message influenced user’s decision-making by what kind of logical trap. It can be fundamental knowledge that is capable of warning the user with predicting logical traps. This paper contributes to providing a novel viewpoint to develop systems for detecting deception of BEC.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. If emails resemble perfectly authentic ones, we suppose that M can have only one type, or all elements in M can be written as “1”. In that sense, Fig. 4 implies that Bob and Charlie can have some reactions when emails resemble imperfectly authentic ones.

References

  1. Jones HS, Towse JN, Race N, Harrison T (2019) Email fraud: the search for psychological predictors of susceptibility. PLoS One 14(1):15

    Google Scholar 

  2. Webster J, Drew JM (2016) Policing advance fee fraud (AFF): experiences of fraud detectives using a victim-focused approach. Int J Police Sci Manag 19(1):39–53

    Article  Google Scholar 

  3. Nizamani S, Memon N, Glasdam M, Nguyen DD (2014) Detection of fraudulent emails by employing advanced feature abundance. Egypt Inf J 15(3):169–174

    Google Scholar 

  4. Aggarwal S, Kumar V, Sudarsan SD (2014) Identification and detection of phishing emails using natural language processing techniques. In: Proceedings of the 7th International Conference on Security of Information and Networks (SIN), 6 pages

  5. Ramachandran A, Dasgupta A, Feamster N, Weinberger K (2011) Spam or ham? characterizing and detecting fraudulent “not spam” reports in web mail systems. In: Proceedings of the 8th Annual Collaboration, Electronic messaging, Anti-Abuse and Spam Conference (CEAS), pp 210–219

  6. Shafqat W, Lee S, Malik S, Kim H (2016) The language of deceivers: linguistic features of crowdfunding scams. In: Proceedings of the 25th International Conference Companion on World Wide Web (WWW), pp 99–100

  7. Everett RM, Nurse JRC, Erola A (2016) The anatomy of online deception: what makes automated text convincing? In: Proceedings of the 31st Annual ACM Symposium on Applied Computing (SAC), pp 1115–1120

  8. Toma CL, Hancock JT (2010) Reading between the lines: linguistic cues to deception in online dating profiles. In: Proceedings of the 2010 ACM conference on Computer supported cooperative work (CSCW), pp 5–8

  9. Medvet E, Kirda E, Kruegel C (2008) Visual-similarity-based phishing detection. In: Proceedings of the 4th International Conference on Security and Privacy in Communication Networks (SecureComm), 6 pages

  10. Dhamija R, Tyger JD, Hearst M (2006) Why phishing works. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI), pp 581–590

  11. Pattanaphanchai J, O’Hara K, Hall W (2013) Trustworthiness criteria for supporting users to assess the credibility of web information. In: Proceedings of the 22nd International Conference on World Wide Web Companion (WWW Companion), pp 1123–1130

  12. Internet Crime Complaint Center (2018) Business E-mail compromise The 12 billion dollar scam. https://www.ic3.gov/media/2018/180712.aspx. Accessed 24 Mar 2020

  13. Nishigaki T, Takenouchi T (2009) The informatic turn-who observes the “Infosphere”? J Socio-Inf 2(1):81–90

    Google Scholar 

  14. Nishigaki T (2008) Fundamental informatics II—for vital organization (in Japanese). NTT Publishing, Tokyo

    Google Scholar 

  15. Barwise J, Seligman J (1997) Information flow -the logic of distributed systems. Cambridge University Press, Cambridge

    Book  Google Scholar 

  16. Internet Crime Complaint Center (IC3) (2016) Business e-mail compromise: the 3.1 billion dollar scam. https://www.ic3.gov/media/2016/160614.aspx. Accessed 24 Mar 2020

  17. Chang EJ, Hussain FK, Dillon TS (2005) Fuzzy nature of trust and dynamic trust modeling in service oriented environments. In: Proceedings of The Workshop on Secure Web Services (SWS), pp 75–83

  18. Ma J, Orgun MA (2006) Trust management and trust theory revision. IEEE Trans Syst Man Cybern Part A 36(3):451–460

    Article  Google Scholar 

  19. Cho JH, Chan K, Adali S (2015) A survey on trust modeling. ACM Comput Surv (CSUR) 48(2):28:1–28:40

    Article  Google Scholar 

  20. Guo J, Chen IR, Jeffrey JP Tsai (2017) A survey of trust computation models for service management in internet of things systems. Comput Commun 97:1–14

    Article  Google Scholar 

  21. Zhong Y, Bhargava B, Lu Y, Angin P (2014) A computational dynamic trust model for user authorization. IEEE Trans Dependable Secure Comput 12(1):1–15

    Article  Google Scholar 

  22. Chenon J, Edomonson W, Esterline A, Neogi N (2014) Formal framework for ensuring consistent system and constraint theories in the design of small satellite systems. In: Proceedings of the Poster Workshop at 5th International Conference on Complex Systems Design & Management (CSD&M), pp 263–281

  23. Bildstein A, Feng J, Bauernhansl T (2018) Information flow-based capability matching service for smart manufacturing. Procedia CIRP 72:1015–1021

    Article  Google Scholar 

  24. Allwein G (2004) A qualitative framework for Shannon information theories. In: Proceedings of Workshop on New Security Paradigms (NSPW), pp 23–31

  25. Schorlemmer M, Kalfoglou Y (2005) Progressive ontology alignment for meaning coordination: an information-theoretic foundation. In: Proceedings of Autonomous Agents and Multiagent Systems (AAMAS), pp 737–744

  26. Atencia M, Schorlemmer M (2007) A formal model for situated semantic alignment. In: Proceedings of Autonomous Agents and Multiagent Systems (AAMAS), pp 1278–1285

  27. Koster A, Sabater-Mir J, Schorlemmer M (2010) Engineering trust alignment: a first approach. In: Proceedings of the 13th International Workshop on Trust in Agent Societies (TRUST), 12 pages

  28. Kawakami H, Suto H, Handa H, Katai O, Shiose T (2008) Analyzing diverse interpretation as benefit of inconvenience. In: Proceedings of International Symposium on Symbiotic Nuclear Power Systems for 21st Century (ISSNP), vol. 2, pp 75–81

  29. Myojin S, Babaguchi N (2019) A logical consideration on deceived person’s thinking. Artif Life Robot (AROB) 24(1):114–118

    Article  Google Scholar 

  30. Shiose T, Motoyoshi T, Toda K, Kawakami H, Katai O (2006) Theoretical analysis of process showing effects for skill succession (in Japanese). Trans Hum Interface Soc 8(4):487–496

    Google Scholar 

  31. Motoyoshi T, Hattori T, Kawakami H, Shiose T, Katai O (2008) A mathematical framework for interpreting playing environments as media for information flow. Adv Hum-Comput Interact 2008:7

    Article  Google Scholar 

  32. Kawakami H (2005) Channel theory and its potential to apply to systems science (in Japanese). Syst Control Inf 49(2):59–63

    Google Scholar 

  33. Suto H, Taniguchi T, Kawakami H (2011) A study of communication scheme for media biotope. In: Proceedings of SICE Annual Conference, pp 206–209

  34. Patitad P, Suto H (2015) A modeling of collaboration mechanism of design process based on channel theory. J Robot Netw Artif Life 2(1):46–49

    Article  Google Scholar 

  35. Gupta G (1994) Chu spaces: a model of concurrency, Ph. D Thesis, Computer Science Department. Stanford University

  36. Mikami Y (2018) Yomiuri online (in Japanese). https://www.yomiuri.co.jp/science/goshinjyutsu/20180109-OYT8T50178.html. Accessed 24 Mar 2020

  37. Yoshino J, Shiga Y, Nikkei staff writers (2017) Nikkei Asian Review. https://asia.nikkei.com/Business/JAL-falls-prey-to-biggest-email-swindle-against-Japan-Inc. Accessed 24 Mar 2020

  38. Kitaoka H (2017) (6) From information to intelligence: the forefront of intelligence studies from the viewpoint of analysis (in Japanese). J Inf Process Manag 60(8):583–588

    Google Scholar 

  39. Otani T (2017) (3) How should we treat with false information on the internet? (in Japanese). J Inf Process Manag 60(5):335–338

    Google Scholar 

  40. Uchida K (2008) The trends of information security psychology and trust—the activities of the information security psychology and the trust (SPT) research group - (in Japanese). IPSJ SIG Tech Rep 2008–CSEC–41(1):1–6

    Google Scholar 

  41. Azaria A, Richardson A, Kraus S (2014) An agent deception detection in discussion based environments (extended abstract). In: Proceedings of the 18th ACM conference on computer supported cooperative work and social computing (AAMAS), pp 1387–1388

  42. Elkins AC, Twyman N, Proudfoot JG, Burgoon JK, Nunamaker JF Jr (2016) Embodied conversational agent-based deception detection. In: Proceedings of SAI intelligent conference, pp 797–803

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Seiko Myojin.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This work was supported by JSPS KAKENHI Grant Number JP16H06302.

This work was presented in part at the 24th International Symposium on Artificial Life and Robotics (Beppu, Oita, January 23–25, 2019).

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Myojin, S., Babaguchi, N. A logical consideration on fraudulent email communication. Artif Life Robotics 25, 475–481 (2020). https://doi.org/10.1007/s10015-020-00597-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10015-020-00597-4

Keywords

Navigation