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Advertising: Machine Learning algorithms to detect anomalies
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| 3.36 MB | Adobe PDF |
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Resumo(s)
Security is a major worry concern nowadays, as the technological development has led to an excessive use of digital devices, where everyone surfs web pages, social networks, blogs, etc. The internet is currently where people spend most of their free time, where they search for and place their information. However, many individuals take advantage of this information for malicious purposes, such as identity, and bank account theft, or even to compromise documents. Furthermore, the methods used not only cause damage to individuals but also affect electronic devices, which become infected with malware, and often become impossible to use again. Consequently, people are becoming progressively worried about digital security, which pushes them to increasingly use software that blocks all kinds of malware. But for the development of Digital Marketing, overcoming these negative consequences becomes a real challenge, as it is affected by ad-blocking software, since most malware is embedded in advertisements, of which criminal minds try to take advantage of. Hence, to overcome the cyber-attacks that can arise from malicious advertisements and prevent internet users from using ad blockers, Digital Marketing will have to find strategies to develop security techniques. With the help of Digital Forensic Science, it is possible to conduct investigations to solve the problems related to digital crime. The expansion of cybersecurity allowed to develop a web extension with which it is possible to block malicious ads, whilst simultaneously allowing for digital advertising not to vanish, but to continue evolving ensuring possible the dissemination of products and information, on which all individuals depend.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
Palavras-chave
Machine Learning Digital Forensics Cybercrime Cybersecurity Advertising UBlock