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Spam Email is the unwanted junk and solicited email sent in bulk to the receivers, using botnets, spambots, or a network of infected computers. These spam emails can be phishing emails that trick users to get their sensitive information, download malware into the user devices or scam the users stealing confidential data. This paper shows a systematic analysis of spam and its types. It also details the procedure of how the spammers get the email addresses of the receivers. It analyses the problems with spamming. A detailed state of the art on spam filtersand the factors that put an email into the spam or ham category is also explained. The paper also discusses spam filtering methods of Gmail, Yahoo, and Outlook. Finally, it brings out several solutions to detect spam using principles of Machine Learning and Data Mining.  \nKeywords: Spam email · Security breach · Naive bayes · Logistic Regression · Machine Learning  \n1 Introduction  \nSpam email is unwanted junk and unsolicited mail sent in bulk to the receiver through an email system like a network of infected computers and botnets. It can also be sent via text messages, phone calls and social media. It can be sent by businesses for commercial reasons. It can also be a malicious attempt to gain access to the user’s computer. Since these emails are sent from botnets, they are very difficult to trace and stop.  \nThe links or attachments in the mail might include malicious information. Generally, the hackers use the links or attachments to check the legitimacy of the email addresses or go to malicious websites or downloads which can install the malware in the computer. The users have their email addresses recognised by  \n2 Razia Sulthana A, Avani Verma, and Jaithunbi A K  \nspambots. Spambots are automated programs that search the internet for email addresses. Thus, spammers use spambots for generating an email distribution list. Emails are generally sent to millions of users. However, only a small number of users react to these emails.  \nThe number of people communicating with each other online is increasing because of the internet. People depend on emails for general or business related issues. It is a very effective tool for communication as it saves cost and time. In recent years, emails are affected by attacks like spam emails, phishing emails etc. Spam floods receivers inboxes with mimicked messages, or with documents or links which can pass on malware to the device or can trick the receivers to reveal their sensitive information. Thus, spam filters are needed to avoid these. The spam filters should provide high accuracy and have minimal errors and should be efficient too. The objectives of the paper include:  \n• Understanding the meaning and types of spam emails.  \n• To analyse the working of spam email filters.  \n• To discuss case studies of Gmail, Yahoo and Outlook spam filters.  \n• To provide solutions to detect spam emails using Machine Learning (ML) algorithms (Naive bayes(NB) and Logistic Regression(LoR)) ..  \n2 Types of Spam  \nSpam can be used for the marketing of goods and services or can be malicious. Types of spam are:  \n1. Phishing Emails - these are sent by cyber attacker to many people which trick people into givin","cbCaitAbxiMznosd","https://ap.wps.com/l/cbCaitAbxiMznosd","pdf",290484,12,"English","# Introduction\n## Types of Spam\n### Understanding how spammers get addresses\n## Spam Filtering Approaches\n## Machine Learning-Based Detection Methods\n## Case Studies: Gmail, Yahoo, Outlook","[{\"question\":\"What problems can spam emails cause for users and organizations?\",\"answer\":\"Spam emails can act as phishing attempts to steal sensitive information and can deliver malware through links or attachments. They also flood inboxes with messages that trick users into exposing confidential data.\"},{\"question\":\"How do spammers typically obtain email addresses?\",\"answer\":\"Spambots are automated programs that search the internet for email addresses. Spammers use them to build email distribution lists for sending messages at scale.\"},{\"question\":\"Which machine learning methods are discussed for detecting spam?\",\"answer\":\"The paper discusses spam detection using machine learning, including Naive Bayes and Logistic Regression.\"}]","A detailed analysis on spam emails and detection using machine learning algorithms | PDF"]