利用机器学习检测垃圾短信

Phanirama Prasad, G Shivaraj, J M Renuka, Janardan Kulkarni, H Aishwarya
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摘要

在我们生活的全球化时代,世界变得越来越小,每个人都彼此相连,电子邮件是实现全球机器和人相互联系的重要工具。近年来,随着通信技术的发展和互联网使用量的激增,电子邮件已成为我们日常生活中不可或缺的一部分。令人遗憾的是,这也导致出现了许多采用网络钓鱼策略诱骗人们披露个人信息的网上骗局。这些骗局可能会导致严重的财务盗窃、身份盗窃、人格暗杀和其他恶意活动,从而对互联网用户造成严重影响。由于这些问题的存在,解决垃圾邮件和网络钓鱼邮件的问题变得至关重要。因此,本项目将利用自然语言处理(NLP)技术检测网络钓鱼和垃圾邮件。让我们探索使用 NLP 识别恶意电子邮件的方法。这有助于检测和分类潜在的有害和垃圾邮件,最终防止对用户数据造成危害。本项目涉及探索如何采用不同的方法来检测垃圾邮件,以及为改进当前和未来可能出现的情况而正在开展的工作,因为诈骗者不断演变,我们需要相应地发展和崛起。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SMS Spam Detection using Machine Learning
Emails are a crucial instrument for achieving the interconnectedness of machines and people worldwide in the global age we live in, when the world is becoming smaller and smaller and everyone is connected to one another. Since the development of communication technology and the exponential increase in internet usage in recent years, emails have become an integral part of our everyday lives. It has also, regrettably, led to the emergence of numerous online scams that employ phishing tactics to trick people into disclosing their personal information. These scams can result in serious financial theft, identity theft, character assassination, and other malicious activities that could have dire repercussions for internet users. Addressing the problem of spam and phishing emails becomes crucial as a result of these problems. Therefore, this project is about detecting phishing and spam e-mails using Natural Language Processing (NLP) techniques. Let's explore methods to identify malicious emails using NLP. This assists in detecting and classifying potentially harmful and spam emails, ultimately preventing harm to user data. This project involves exploration of how different methods are implemented to detect the spam e-mails and the work being done to improve upon the current and possible future scenarios because as the scammers keep evolving and we need to develop and rise up accordingly
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