Malicious spam injection attack detection on social webpage posts

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Abstract

The social media platforms for teens and genz are highly influential; 39% state that they will use' buy buttons' and 25% use smartphones for shopping images. In the meantime, 28 percent of US internet users between 18 and 55 years of age said their aim is to buy via social media during holidays.As these channels become more central to our everyday lives, social media platforms have now become a key vector of attack that businesses cannot neglect anymore. Social media Platforms provide up to 20% more options for delivering malware for consumers, such as advertising, social engineering, equities and plug-ins compare to eCommerce and corporate websites.The suggested version Supervised SD-LVQ used to detect malicious firmware on various social media sites. LVQ classifies the different service calls attacks associated with XML, HTML, JavaScript files and different forms of malicious attacks on social networks. The test results show that 98.70% is genuinely positive and 0.02% is falsely negative.

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APA

Arul, E., & Punidha, A. (2020). Malicious spam injection attack detection on social webpage posts. Advances in Parallel Computing, 37, 474–478. https://doi.org/10.3233/APC200187

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