Skip to main content

Paradoks Hukum Rekayasa Sosial Pig Butchering Scam Dalam Investasi Digital Aset Kripto

Ashibly, Ashibly (2025) — Jurnal Hukum IUS QUIA IUSTUM

Citation activity

Total citations · Google Scholar
Unavailable
Average per calendar year
Citation count unavailable

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: 10.20885/iustum.vol32.iss3.art4 (opens in a new tab)

Type:   Journal Article
Country:   Indonesia
Tags:   AI-Enabled Fraud, Cross Border Cybercrime, Cross Cultural, Crypto Investment Fraud, Crypto Regulation, Indonesia, Money Mules, Mutual Legal Assistance, Offender Tactics, Pig Butchering, Romance Baiting, Social Engineering
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 normative legal study analyzes legislation, regulations, doctrine, and secondary legal literature concerning social engineering in cryptocurrency pig-butchering scams. It organizes the scheme into three operational stages: hunting, in which an offender approaches a target through a false identity; fattening or care, in which daily messages and relationship promises build trust; and slaughter, in which the relationship is converted into financial extraction. The article uses this process to examine tensions in applying existing legal concepts to digitally mediated manipulation and investment fraud. It is a conceptual and doctrinal analysis, not an empirical study of victims, offenders, platforms, transactions, investigations, or court outcomes, so the three-stage description is an analytical model rather than a prevalence finding.

          

        
                  

            
Identified Gaps

            
Prior research is described as lacking an international-regulatory response to social-engineering pig-butchering scams in crypto investment. The paper further identifies no international legal instrument specifically targeting this organized, transnational crime, alongside gaps in cross-border investigation, prosecution, information exchange, and asset recovery.

          

        
                  

            
Methods

            
This normative legal study uses a conceptual approach. It examines primary legal materials (relevant legislation and regulations) and secondary materials including legal books, journals, doctrines, and legal research. Data were gathered through library study of legal norms, rules, the legal system, and related literature, then qualitatively analyzed through interpretation and descriptive understanding of written legal materials.

          

        
                  

            
Limitations

            
The study is a normative, conceptual legal analysis based on secondary legal materials, rather than an empirical study of victims, offenders, platforms, or enforcement agencies. Its conclusions on operational barriers and victim experiences therefore rely on legal interpretation, cited literature, and illustrative cases; the text does not report systematic primary-data collection or comparative analysis across jurisdictions.

          

        
                  

            
Future Work

            
Use comparative legal research on cross-border regulation, prevention, and enforcement for crypto-asset investment pig-butchering scams.

          

              

    
    

        
Related Research Insights

        

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