Abstract
In the emerging field of Meta Computing, where data collection and integration are essential components, the threat of adversary hidden link attacks poses a significant challenge to web crawlers. In this paper, we investigate the impact of these attacks on data collection by web crawlers, emphasizing their evasion of traditional detection methods. Through empirical evaluation, we uncover vulnerabilities in existing crawler mechanisms, particularly in code inspection, and propose enhancements to mitigate these weaknesses. Our assessment of real-world web pages reveals the prevalence and impact of adversary hidden link attacks, emphasizing the necessity for robust countermeasures. Furthermore, we introduce a mitigation framework that integrates element visual inspection techniques. Our evaluation demonstrates the framework's efficacy in detecting and addressing these advanced cyber threats within the evolving landscape of Meta Computing.
Recommended Citation
J. Xiong et al., "Adversarial Hidden Link Threats In Meta Computing," Proceedings 2024 International Conference on Meta Computing Icmc 2024, pp. 23 - 34, Institute of Electrical and Electronics Engineers, Jan 2024.
The definitive version is available at https://doi.org/10.1109/ICMC60390.2024.00010
Department(s)
Computer Science
Keywords and Phrases
Adversary Hidden Link; Content Deception Detection; Data Integration; Meta Computing; Web Crawling
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2024
