Skip to main content

A Game-Theoretic Approach to Detecting Romance Scams

Ebelechukwu Nwafor (2023) — New Perspectives in Behavioral Cybersecurity

View Original Source (opens in a new tab)

DOI: 10.1201/9781003415060-19 (opens in a new tab)

Type:   Book Chapter
Country:   United States
Tags:   Automated Detection, Dating Scams, Financial Theft, Game Theory, Human Moderation, Minimax Regret, Online Dating, Romance Scams
What do these research terms mean?
Preprint
A manuscript shared before formal peer review and publication. Check whether a later published version is available.
Dataset
A collection of data or examples for others to inspect or reuse. It can appear in Library search and topic mapping, but RSRC does not use dataset records as evidence in Research Insights.
Dissertation or thesis
Research submitted for an academic degree. This describes its format, not its reliability.
Journal article
An article published in a journal. This label alone does not establish peer review, study quality, or how well the findings apply elsewhere.
Qualitative research
Examines experiences, meanings, or processes, often through interviews or observations. It can explain how something happens without estimating how common it is.
Quantitative research
Uses numerical measurements to describe patterns or test relationships. A relationship between two measurements does not by itself show that one causes the other.
Systematic review
Uses a planned, documented method to find and assess research addressing a question. Its conclusions still depend on the included studies and what the search covered.
Meta-analysis
Statistically combines results from multiple studies. Combining studies does not remove weaknesses in their design or make unlike populations interchangeable.
Not classified
This record has no recognized label in this filter. It does not mean the publication used no method, or that no research exists.

Definitions draw on DataCite resource types; Cochrane review methods; NLM: association and causation. RSRC’s dataset and classification rules are explained in our methodology.

Citation tools
Download RIS Download BibTeX 


              
              

            

          

        


      

      

    

        
Transparency

        
Evidence and review status

        
This page contains AI-generated content. No human content review or subject-matter-expert review is recorded.

    


    

                    

                
Source basis

                

                    Downloaded PDF
                

            

                    

                
Source updates

                

                    No notice found at last check
                

            

                    

                
AI-generated page content

                

                    Yes
                

            

                    

                
Automated checks

                

                    Passed
                

            

                    

                
Administrative approval

                

                    Yes
                

            

                    

                
Human content review

                

                    Not recorded
                

            

                    

                
Subject-matter-expert review

                

                    Not recorded
                

            

            


    

        
            How this was prepared
        
        

                            

                    
Source basis

                    

                    
RSRC downloaded and privately stored a copy of the paper for internal analysis. The PDF is not offered to viewers from this page.


                                            
    
                                                            
  • 
                                    PDF added to RSRC:
                                    
                                
    • 
                                                    

                    
                                        

                

                            

                    
Source updates

                    

                    
No incoming update notice was found in the dated Crossref response. Coverage is incomplete, particularly for corrections and expressions of concern; this is not a guarantee that the source is valid or unchanged.


                                            
    
                                                            
  • 
                                    Last source-status attempt:
                                    
                                
    • 
                                                    

                    
                                        

                

                            

                    
AI-generated page content

                    

                    
AI-generated research notes displayed on this page: Synopsis, Identified gaps, Methods, Limitations, Future work. The paper itself is not described as AI-generated.


                                            
    
                                                            
  • 
                                    Document analysis recorded:
                                    
                                
    • 
                                                            
  • 
                                    Page record updated:
                                    
                                
    • 
                                                    

                    
                                        

                

                            

                    
Automated checks

                    

                    
The current, source-bound synopsis passed the recorded versioned publication checks.


                                            
    
                                                            
  • 
                                    Checks completed:
                                    
                                
    • 
                                                    

                    
                                            

                            
                                View passed checks (3)
                            
                            
    
                                                                    
  • Length, completeness, repetition, refusal, boilerplate, and active-markup screening
    • 
                                                                    
  • Numerical claims checked against the available source text
    • 
                                                                    
  • English-source lexical grounding check
    • 
                                                            

                        

                                        

                

                            

                    
Administrative approval

                    

                    
The record is approved for public display, but a complete historical administrator action is not recorded.


                    
                                        

                

                            

                    
Human content review

                    

                    
No human review is recorded for the AI-generated content displayed on this page.


                    
                                        

                

                            

                    
Subject-matter-expert review

                    

                    
RSRC has not recorded review of this content by a subject-matter or methods expert.


                    
                                        

                

                    

    


    

        Review-state definitions

        Found a possible error?
        Request a correction.
    



    



              

        
                  

            
Synopsis

            
This conceptual chapter explains how game theory could model strategic interaction between romance scammers, targets, and detection systems. It argues that an automated detector informed by game-theoretic incentives and likely responses could help identify deception, reduce financial and personal-information theft, and improve trust in online dating services. The accessible abstract presents a modeling approach and anticipated benefits, not a completed deployment. It does not describe a dataset, implementation, comparison baseline, or measured detection performance. The chapter should therefore be treated as a proposed analytical direction for romance-scam detection rather than evidence that a particular automated system is effective.

          

        
                  

            
Identified Gaps

            
The paper identifies the difficulty of scaling human moderation as online dating interactions increase and notes inconsistent moderation policies across geographical regions. It proposes automation supported by human review, but does not provide evidence on how the model performs in operational settings.

          

        
                  

            
Methods

            
The paper presents a conceptual game-theoretic model of a romance scam using the minimax-regret criterion. It defines victim and scammer actions in a simplified $100 payment-request scenario, constructs a normal-form payoff matrix, converts entries into regret values, and identifies a minimax-regret value associated with selected actions.

          

        
                  

            
Limitations

            
The work is an illustrative mathematical overview based on a single simplified scenario. It reports no empirical dataset, implementation, validation experiment, comparison with alternative detectors, or measured detection accuracy. Its payoff values and assumptions about victim and scammer behavior are presented without supporting empirical justification.

          

        
                  

            
Future Work

            
Future research should empirically test the proposed minimax-regret model on real dating-platform interactions, assess false-positive and false-negative outcomes under human review, and compare it with existing moderation approaches.

          

              

    
    

        
Related Research Insights

        

            See how this publication connects to RSRC's living evidence syntheses through current citations and research-topic mapping.