ConvXSS: A deep learning-based smart ICT framework against code injection attacks for HTML5 web applications in sustainable smart city infrastructure
نویسندگان
چکیده
In this paper we propose ConvXSS, a novel deep learning approach for the detection of XSS and code injection attacks, followed by context-based sanitization malicious if model detects any in application. Firstly, briefly discuss attacks that might pose threat to sustainable smart cities. Along with this, various approaches proposed previously alleviation these their respective limitations. Then our adopting whose novelty is based on Data Pre-Processing. finally Context-based Sanitization replace part sanitized code. Numerical experiments conducted datasets have shown results out which best has an accuracy 99.42%, precision 99.81% recall 99.35%. When compared other state art techniques domain, shows at par or case, better terms speed CSS attacks.
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ژورنال
عنوان ژورنال: Sustainable Cities and Society
سال: 2022
ISSN: ['2210-6707', '2210-6715']
DOI: https://doi.org/10.1016/j.scs.2022.103765