Published September 13, 2022 | Version v1
Journal article Open

PROTECTING AGAINST MALICIOUS CODE INJECTION IN REVIEWS ON WEB APPLICATIONS

Authors/Creators

Description

Malicious code injection is done by the attackers or hackers mainly in reviews, these are
the fake user identities that are created by the attackers, through sending continuous links
to some user till the user clicks on that link. When user clicks the link, that particular users
identity will be stolen by the attackers which is done like the phishing, generally these
reviews which are maliciously injected are mixed with the original users review of the
product in a website. To identify these malicious injection attacked reviews, in this paper
the Naive Bayes Classifier algorithm is used. Then to eliminate the unwanted disturbed
data in the website the Natural Language Processing technique is used. The Natural
Language Processing technique, which removes unwanted data by understanding the text
or words in review. Then the length of the reviews in the given sample dataset is reduced
for easy understanding by using the Principal Component Analysis algorithm which
reduces the dimensionality of the reviews. Then user input review is compared with the
sample dataset and classified as good review and bad review and also detected as malicious
or not by using the Naïve Bayes Classifier algorithm which is used for the classification of
the objects.

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References

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