Mostrar el registro sencillo del ítem
dc.contributor.author | Guo, You![]() |
es_ES |
dc.contributor.author | Marco-Gisbert, Héctor![]() |
es_ES |
dc.contributor.author | Keir, Paul![]() |
es_ES |
dc.date.accessioned | 2021-11-11T19:30:57Z | |
dc.date.available | 2021-11-11T19:30:57Z | |
dc.date.issued | 2020-01 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/176997 | |
dc.description.abstract | [EN] A webshell is a command execution environment in the form of web pages. It is often used by attackers as a backdoor tool for web server operations. Accurately detecting webshells is of great significance to web server protection. Most security products detect webshells based on feature-matching methods-matching input scripts against pre-built malicious code collections. The feature-matching method has a low detection rate for obfuscated webshells. However, with the help of machine learning algorithms, webshells can be detected more efficiently and accurately. In this paper, we propose a new PHP webshell detection model, the NB-Opcode (naive Bayes and opcode sequence) model, which is a combination of naive Bayes classifiers and opcode sequences. Through experiments and analysis on a large number of samples, the experimental results show that the proposed method could effectively detect a range of webshells. Compared with the traditional webshell detection methods, this method improves the efficiency and accuracy of webshell detection | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Future Internet | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Webshell attacks | es_ES |
dc.subject | Machine learning | es_ES |
dc.subject | Naive Bayes | es_ES |
dc.subject | Opcode sequence | es_ES |
dc.subject.classification | ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES | es_ES |
dc.title | Mitigating Webshell Attacks through Machine Learning Techniques. | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/fi12010012 | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors | es_ES |
dc.description.bibliographicCitation | Guo, Y.; Marco-Gisbert, H.; Keir, P. (2020). Mitigating Webshell Attacks through Machine Learning Techniques. Future Internet. 12(1):1-16. https://doi.org/10.3390/fi12010012 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/fi12010012 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 16 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 12 | es_ES |
dc.description.issue | 1 | es_ES |
dc.identifier.eissn | 1999-5903 | es_ES |
dc.relation.pasarela | S\439340 | es_ES |