Preventing Poisoning Attacks On AI Based Threat Intelligence Systems
Title | Preventing Poisoning Attacks On AI Based Threat Intelligence Systems |
Publication Type | Conference Paper |
Year of Publication | 2019 |
Authors | Khurana, N., Mittal, S., Piplai, A., Joshi, A. |
Conference Name | 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing (MLSP) |
Date Published | Oct. 2019 |
Publisher | IEEE |
ISBN Number | 978-1-7281-0824-7 |
Keywords | AI Poisoning, AI systems, artificial intelligence, computer security, cybersecurity domain, Engines, ensembled semi-supervised approach, Human Behavior, learning (artificial intelligence), malicious information, online social media, poisoning attacks prevention, pubcrawl, resilience, Resiliency, Scalability, security analysts, security of data, social networking (online), Support vector machines, threat intelligence systems, Twitter, Web sites |
Abstract | 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. |
URL | https://ieeexplore.ieee.org/document/8918803 |
DOI | 10.1109/MLSP.2019.8918803 |
Citation Key | khurana_preventing_2019 |
- poisoning attacks prevention
- Web sites
- threat intelligence systems
- Support vector machines
- social networking (online)
- security of data
- security analysts
- Scalability
- Resiliency
- resilience
- pubcrawl
- AI Poisoning
- online social media
- malicious information
- learning (artificial intelligence)
- Human behavior
- ensembled semi-supervised approach
- Engines
- cybersecurity domain
- computer security
- Artificial Intelligence
- AI systems