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How to Hide One's Relationships from Link Prediction Algorithms
Marcin Waniek1,2, Kai Zhou3, Yevgeniy Vorobeychik3
1Computer Science, New York University, Abu Dhabi, UAE.
Scientific Reports
|August 23, 2019
Summary
Individuals can protect private social network connections from link prediction algorithms. Strategic "unfriending" is more effective than adding connections to conceal sensitive relationships, empowering users to safeguard their privacy online.
Area of Science:
- Social Network Analysis
- Cybersecurity
- Privacy Protection
Background:
- Link prediction algorithms can expose private connections on social networks.
- Current mitigation strategies focus on central authorities, neglecting individual user actions.
- Individuals lack methods to proactively protect their sensitive relationships online.
Purpose of the Study:
- To investigate how individuals can rewire their network neighborhood to hide sensitive relationships.
- To develop practical heuristics for social media users to conceal connections.
- To analyze the effectiveness of different network manipulation strategies.
Main Methods:
- Proved the NP-completeness of optimally hiding relationships.
- Developed and evaluated heuristic-based strategies for network rewiring.
- Empirically tested strategies on a large-scale telecommunication network (248,763 individuals, 829,725 calls).
Main Results:
- Optimal relationship hiding is computationally infeasible.
- Strategic "unfriending" of a few individuals is highly effective in concealing sensitive links.
- Random rewiring can inadvertently expose relationships; strategic manipulation is crucial.
- Smaller, denser networks are more susceptible to link prediction algorithm manipulation.
Conclusions:
- Individuals can actively protect their private connections using strategic network rewiring.
- Focusing on targeted unfriending offers a practical and effective privacy-preserving approach.
- Understanding network structure is key to mitigating privacy risks from link prediction.
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