Statically identifying XSS using deep learning-Reference-Cited by-同舟云学术

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Statically identifying XSS using deep learning

Published:2022-07 Issue: Volume:219 Page:102810
ISSN:0167-6423
Container-title:Science of Computer Programming
language:en
Short-container-title:Science of Computer Programming

Author:

Maurel Heloise,Vidal Santiago,Rezk Tamara

Funder

Horizon 2020 European Innovation Council Fast Track to Innovation

ANR

Publisher

Elsevier BV

Subject

Software

Reference40 articles.

1. XSS Exploits: Cross Site Scripting Exploits and Defense;Fogie,2007

2. Fast and precise sanitizer analysis with BEK;Hooimeijer,2011

3. Saner: composing static and dynamic analysis to validate sanitization in web applications;Balzarotti,2008

4. Noncespaces: using randomization to enforce information flow tracking and thwart cross-site scripting attacks;Gundy,2009

5. Automated code injection prevention for web applications;Luo,2011

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1. Swift Detection of XSS Attacks: Enhancing XSS Attack Detection by Leveraging Hybrid Semantic Embeddings and AI Techniques;Arabian Journal for Science and Engineering;2024-06-03

2. Twenty-two years since revealing cross-site scripting attacks: A systematic mapping and a comprehensive survey;Computer Science Review;2024-05

3. Personal data filtering: a systematic literature review comparing the effectiveness of XSS attacks in web applications vs cookie stealing;Annals of Telecommunications;2024-04-18

4. Prototyping an Agent for Dynamic Generation of Attack-Payloads in Web Application Vulnerability Assessment;2023 15th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter);2023-12-11

5. A Hybrid Dynamic Testing technology source code XSS vulnerability detection method;2023 IEEE Smart World Congress (SWC);2023-08-28

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