• Corpus ID: 239768614

Fairness Degrading Adversarial Attacks Against Clustering Algorithms

@article{Chhabra2021FairnessDA,
  title={Fairness Degrading Adversarial Attacks Against Clustering Algorithms},
  author={Anshuman Chhabra and Adish Kumar Singla and Prasant Mohapatra},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.12020}
}
Clustering algorithms are ubiquitous in modern data science pipelines, and are utilized in numerous fields ranging from biology to facility location. Due to their widespread use, especially in societal resource allocation problems, recent research has aimed at making clustering algorithms fair, with great success. Furthermore, it has also been shown that clustering algorithms, much like other machine learning algorithms, are susceptible to adversarial attacks where a malicious entity seeks to… 
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