دورية أكاديمية
Few-Shot API Attack Detection: Overcoming Data Scarcity with GAN-Inspired Learning ...
| العنوان: | Few-Shot API Attack Detection: Overcoming Data Scarcity with GAN-Inspired Learning ... |
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| المؤلفون: | Aharon, Udi, Marbel, Revital, Dubin, Ran, Dvir, Amit, Hajaj, Chen |
| بيانات النشر: | arXiv |
| سنة النشر: | 2024 |
| المجموعة: | DataCite Metadata Store (German National Library of Science and Technology) |
| مصطلحات موضوعية: | Cryptography and Security cs.CR, FOS Computer and information sciences |
| الوصف: | Web applications and APIs face constant threats from malicious actors seeking to exploit vulnerabilities for illicit gains. These threats necessitate robust anomaly detection systems capable of identifying malicious API traffic efficiently despite limited and diverse datasets. This paper proposes a novel few-shot detection approach motivated by Natural Language Processing (NLP) and advanced Generative Adversarial Network (GAN)-inspired techniques. Leveraging state-of-the-art Transformer architectures, particularly RoBERTa, our method enhances the contextual understanding of API requests, leading to improved anomaly detection compared to traditional methods. We showcase the technique's versatility by demonstrating its effectiveness with both Out-of-Distribution (OOD) and Transformer-based binary classification methods on two distinct datasets: CSIC 2010 and ATRDF 2023. Our evaluations reveal consistently enhanced or, at worst, equivalent detection rates across various metrics in most vectors, highlighting the ... : 8 pages, 2 figures, 7 tables ... |
| نوع الوثيقة: | article in journal/newspaper report |
| اللغة: | unknown |
| DOI: | 10.48550/arxiv.2405.11258 |
| الإتاحة: | https://doi.org/10.48550/arxiv.2405.11258Test https://arxiv.org/abs/2405.11258Test |
| حقوق: | Creative Commons Attribution Non Commercial No Derivatives 4.0 International ; https://creativecommons.org/licenses/by-nc-nd/4.0/legalcodeTest ; cc-by-nc-nd-4.0 |
| رقم الانضمام: | edsbas.860F0DA4 |
| قاعدة البيانات: | BASE |
| DOI: | 10.48550/arxiv.2405.11258 |
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