Skip to main content

Crypto-Cognitive Exploitation: Integrating Cognitive, Social, and Technological perspectives on cryptocurrency fraud

Arif Perdana ; Hee Jhee Jiow (2024) — Telematics and Informatics

Citation activity

Total citations · Google Scholar
21
Average per calendar year
7.0

Count checked .

21 citations ÷ 3 calendar years (2024–2026). The first and last years may be partial. This is a lifetime average, not a year-by-year citation history.

Counts reflect Google Scholar’s coverage and do not measure research quality. Source, calculation and limitations

View Original Source (opens in a new tab)

DOI: 10.1016/j.tele.2024.102191 (opens in a new tab)

Type:   Journal Article
Country:   Global
Tags:   AI Enabled Analysis, Cognitive Vulnerability, Cryptocurrency Fraud, Defi Scams, Dfpi Reports, Fraudulent Trading Platforms, LLM Assisted Coding, Pig Butchering, Pig Butchering Scams, Prevention, Regulatory Strategies, Romance Scams, Social Engineering, Text Analytics
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

                    

                    
An authenticated administrator approved the bibliographic record for public Library display. This is not a review of every research claim.


                                            
    
                                                            
  • 
                                    Approved for public display:
                                    
                                
    • 
                                                    

                    
                                        

                

                            

                    
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 study applied cognitive-vulnerability and social-engineering theories to 204 cryptocurrency-scam reports from California's Department of Financial Protection and Innovation. Advanced language-model coding achieved an interrater kappa of 0.78, identified seven scam dimensions, and informed the proposed Crypto-Cognitive Exploitation Model. Fraudulent trading-platform schemes appeared in more than 80% of reports, while pig-butchering appeared in more than 50% and frequently co-occurred with platform fraud. Reported consequences included lost savings, debt, betrayal, shame, and diminished trust; offenders also invoked AI or automated trading to promise returns. A single U.S. reporting source, reporting and narrative bias, automated-coding error, API constraints, and no longitudinal validation limit the model's external validity.

          

        
                  

            
Identified Gaps

            
Explicit gaps include reliance on 204 DFPI reports and Chainalysis API limitations; absence of multi-source data; limited generalizability to non-US contexts; lack of longitudinal data; need empirical validation of CCEM; need to translate findings into cross-jurisdictional prevention and policy evaluations.

          

        
                  

            
Methods

            
An integrated theoretical framework combining Cognitive Vulnerability Theory and the Social Engineering Approach analyzes 204 DFPI cryptocurrency scam reports to map scam dimensions. The study uses advanced language models for data coding, achieving interrater reliability (kappa = 0.78) and introduces the Crypto-Cognitive Exploitation Model (CCEM). It identifies seven scam dimensions and notes prevalent fraudulent trading platform scams often co-occur with pig butchering.

          

        
                  

            
Limitations

            
Limitations include reliance on a single US-based data source (DFPI) and Chainalysis API restrictions, potential reporting bias, and narrative variability; limited generalizability to global contexts; no longitudinal tracking; potential measurement error from automated coding; need external validation of CCEM.

          

        
                  

            
Future Work

            
Future research should broaden data sources beyond US DFPI reports to capture global scam typologies and cross-jurisdictional responses. Validate and extend the Crypto-Cognitive Exploitation Model (CCEM) using multi-source datasets (global Chainalysis data, consumer complaint portals) and longitudinal data to track scam evolution. Empirically test the effectiveness of recommended digital strategies and regulatory countermeasures across different regulatory regimes. Investigate victim demographics and psychosocial factors to tailor prevention messaging. Develop standardized coding schemes for scam reports to improve comparability. Explore real-time detection tools and interventions in DeFi and exchange ecosystems, and assess policy impact on scam incidence and recovery outcomes.

          

              

    
    

        
Related Research Insights

        

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