Skip to main content

Can I believe you? Establishing Trust in Computer Mediated Introductions

Borke Obada-Obieh ; Anil Somayaji (2017) — Proceedings of the 2017 New Security Paradigms Workshop (NSPW 2017)

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: 10.1145/3171533.3171544 (opens in a new tab)

Country:   Global
Tags:   Computer Mediated Introductions, Dating Platform Safety, Identity Verification, Online Dating, Prevention, Privacy, Reputation Systems, Trust
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

                

                    Unresolved
                

            

                    

                
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

                    

                    
The latest source-status check did not establish whether an incoming update notice exists. Missing metadata or provider access does not establish source validity.


                                            
    
                                                            
  • 
                                    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:
                                    
                                
    • 
                                                            
  • 
                                    Synopsis generation 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 publication critically examines how trust is established in computer mediated introductions (CMI), defined as online interactions between strangers that aim to lead to in-person meetings. The authors distinguish two CMIs: business CMIs, where online introductions precede offline transactions for goods or services, and personal CMIs, where introductions are for social connections or dating. They argue that trust signals that work in routine online business interactions do not reliably translate to personal CMIs, where risk and stakes in a real-life meeting are higher. The work analyzes trust mechanisms across three dating platforms—Match.com, Plenty of Fish (POF), and Tinder—and situates them within a broader literature on reputation, identity authenticity, and privacy in online dating. Methodologically, the authors conduct a structured comparison of how these platforms handle trust signals, including information requirements, identity verification, protection of user data, and mechanisms for handling blocking and privacy. They also synthesize findings from prior research on multimedia cues, reputation systems, and cryptographic approaches relevant to CMIs. The core finding is that existing mechanisms on these sites do not provide robust, trustworthy assurances about who a potential date truly is, or about the safety of meeting offline. The paper argues that attackers can exploit gaps such as unverifiable identities, incomplete or easily falsified profiles, and cross-platform privacy weaknesses, and that even paid tiers or social-media-based verification do not fully solve the problem. To address these gaps, the authors propose alternative trust mechanisms for personal CMIs, including live, on-site verification steps, multimedia authentication features, and clearer “verified” status indicators. They emphasize evaluating proposed measures with user studies and caution about scale, privacy, and potential new avenues for misuse. The work stops short of prescribing definitive solutions, instead outlining a research agenda to strengthen trust in computer mediated introductions.

          

        
                  

            
Identified Gaps

            
Computer-mediated introductions are presented as an understudied computer-security problem. Existing dating-platform trust signals, including profiles, photos, social-media accounts, login activity, and completeness indicators, are described as easily manufactured and insufficient against malicious actors. The paper also identifies a lack of effective ways to obtain adequate user feedback after offline meetings.

          

        
                  

            
Methods

            
The paper develops a threat model for online dating and critically analyzes trust mechanisms on Match.com, Plenty of Fish, and Tinder. It compares observed platform features with an idealized set of introduction-service responsibilities, synthesizes relevant trust and reputation literature, and proposes alternative mechanisms for identity verification, communication, safety response, and interaction ratings.

          

        
                  

            
Limitations

            
This is a conceptual and comparative analysis rather than a direct evaluation of user outcomes or offender behavior. Its platform assessment is limited to three services and the features described at the time of study. The authors state that evaluating new mechanisms through post-meeting user feedback would be difficult because feedback incentives are weak and research faces cost, scale, and invasiveness challenges.

          

        
                  

            
Future Work

            
Conduct user studies and develop technical mechanisms specialized for computer-mediated introductions. Evaluate whether proposed security mechanisms improve online-dating safety, ideally using feedback after offline meetings. Develop effective, scalable, and minimally invasive methods for obtaining post-meeting feedback so patterns of fraud or misrepresentation can be addressed.

          

              

    
    

        
Related Research Insights

        

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