mlsanityData to 7 Oct 2026

Preventing Poisoning Attacks on AI based Threat Intelligence Systems

arXiv 1807.07418 ↗First posted 19 Jul 2018cs.SI cs.CR cs.LGcited by 4

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Abstract (arXiv)

As AI systems become more ubiquitous, securing them becomes an emerging challenge. Over the years, with the surge in online social media use and the data available for analysis, AI systems have been built to extract, represent and use this information. The credibility of this information extracted from open sources, however, can often be questionable. Malicious or incorrect information can cause a loss of money, reputation, and resources; and in certain situations, pose a threat to human life. In this paper, we use an ensembled semi-supervised approach to determine the credibility of Reddit posts by estimating their reputation score to ensure the validity of information ingested by AI systems. We demonstrate our approach in the cybersecurity domain, where security analysts utilize these systems to determine possible threats by analyzing the data scattered on social media websites, forums, blogs, etc.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Jul 2018.

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Citing papers per year: 2021: 1; 2022: 0; 2023: 2; 2024: 1.

4 papers.