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PGM-index learned index vulnerable to size-inflating poisoning attacks

By PulseAugur Editorial · [1 sources] ·

Researchers have identified a significant vulnerability in the PGM-index, a popular learned index structure. A new attack, termed PGM-attack, can drastically inflate the index size by up to 120x by inserting adversarial keys. This attack exploits the index's optimization objective, demonstrating that even theoretically optimal structures can be susceptible to poisoning. The findings suggest a need for robustness-aware design in future learned indexes. AI

RANK_REASON The cluster contains a research paper detailing a new attack on a specific data structure. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

PGM-index learned index vulnerable to size-inflating poisoning attacks

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The cluster contains a research paper detailing a new attack on a specific data structure. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Atsuki Sato, Martin Aum\"uller, Yusuke Matsui ·

    Poisoning Attacks on the PGM-index

    arXiv:2609.02328v1 Announce Type: cross Abstract: The PGM-index (Ferragina and Vinciguerra, VLDB'20) is one of the most practical learned indexes, owing to its theoretical elegance and consistently strong empirical performance. It is built on optimal piecewise linear approximatio…

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