Bio inspired email spam detection: A quantitative investigation
Spam has long been used by criminals to conduct illegal online operations including stealing personal information, selling counterfeit goods, and spreading malware. Spammer is a term used to describe someone who creates spam. Spamming is carried out in the following ways: Advertising, sending messag...
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description | Spam has long been used by criminals to conduct illegal online operations including stealing personal information, selling counterfeit goods, and spreading malware. Spammer is a term used to describe someone who creates spam. Spamming is carried out in the following ways: Advertising, sending messages to the same website multiple times, are all examples of spam. Spam has become the preferred method for cyber criminals to propagate harmful software. Due to the disclosure of information to unauthorized parties, collaborative detection has implications for email privacy. Due to the large number of emails exchanged between users, spam identification is challenging. Pop-ups that appear in the form of internet advertising are also difficult to ignore. It is often a tiny window, which emerges abruptly in front of a display area. This study presents a comparison of several Bio Inspired spam detection algorithms. |
doi_str_mv | 10.1063/5.0217037 |
format | Conference Proceeding |
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A. S. ; Rajesh, A.</creator><contributor>Godfrey Winster, S ; Pushpalatha, M ; Baskar, M ; Kishore Anthuvan Sahayaraj, K</contributor><creatorcontrib>Vinoth, N. A. S. ; Rajesh, A. ; Godfrey Winster, S ; Pushpalatha, M ; Baskar, M ; Kishore Anthuvan Sahayaraj, K</creatorcontrib><description>Spam has long been used by criminals to conduct illegal online operations including stealing personal information, selling counterfeit goods, and spreading malware. Spammer is a term used to describe someone who creates spam. Spamming is carried out in the following ways: Advertising, sending messages to the same website multiple times, are all examples of spam. Spam has become the preferred method for cyber criminals to propagate harmful software. Due to the disclosure of information to unauthorized parties, collaborative detection has implications for email privacy. Due to the large number of emails exchanged between users, spam identification is challenging. 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S.</creatorcontrib><creatorcontrib>Rajesh, A.</creatorcontrib><title>Bio inspired email spam detection: A quantitative investigation</title><title>AIP conference proceedings</title><description>Spam has long been used by criminals to conduct illegal online operations including stealing personal information, selling counterfeit goods, and spreading malware. Spammer is a term used to describe someone who creates spam. Spamming is carried out in the following ways: Advertising, sending messages to the same website multiple times, are all examples of spam. Spam has become the preferred method for cyber criminals to propagate harmful software. Due to the disclosure of information to unauthorized parties, collaborative detection has implications for email privacy. Due to the large number of emails exchanged between users, spam identification is challenging. Pop-ups that appear in the form of internet advertising are also difficult to ignore. It is often a tiny window, which emerges abruptly in front of a display area. This study presents a comparison of several Bio Inspired spam detection algorithms.</description><subject>Advertising</subject><subject>Algorithms</subject><subject>Counterfeit</subject><subject>Electronic mail</subject><subject>Spamming</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2024</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNotkEtLA0EQhAdRMEYP_oMFb8LG7nmvF4nBFwS85OBtmJ2dyITsIzuzAf99NianhuqPqqIIuUeYIUj2JGZAUQFTF2SCQmCuJMpLMgEoeE45-7kmNzFuAGihlJ6Ql9fQZqGJXeh9lfnahm0WO1tnlU_epdA2z9k82w22SSHZFPZ-pPc-pvBrj99bcrW22-jvzndKVu9vq8Vnvvz--FrMl3knmcorAOk0VBVT3pYgmC0qXlJuGTDtHAoUQBVnqK1cOweopHTISy1GSWHBpuThZNv17W4Y482mHfpmTDQMtFCUUw0j9Xiiovsv2zam60Nt-z-DYI77GGHO-7ADkVVVlQ</recordid><startdate>20240729</startdate><enddate>20240729</enddate><creator>Vinoth, N. A. 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S.</au><au>Rajesh, A.</au><au>Godfrey Winster, S</au><au>Pushpalatha, M</au><au>Baskar, M</au><au>Kishore Anthuvan Sahayaraj, K</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Bio inspired email spam detection: A quantitative investigation</atitle><btitle>AIP conference proceedings</btitle><date>2024-07-29</date><risdate>2024</risdate><volume>3075</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>Spam has long been used by criminals to conduct illegal online operations including stealing personal information, selling counterfeit goods, and spreading malware. Spammer is a term used to describe someone who creates spam. Spamming is carried out in the following ways: Advertising, sending messages to the same website multiple times, are all examples of spam. Spam has become the preferred method for cyber criminals to propagate harmful software. Due to the disclosure of information to unauthorized parties, collaborative detection has implications for email privacy. Due to the large number of emails exchanged between users, spam identification is challenging. Pop-ups that appear in the form of internet advertising are also difficult to ignore. It is often a tiny window, which emerges abruptly in front of a display area. This study presents a comparison of several Bio Inspired spam detection algorithms.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0217037</doi><tpages>6</tpages></addata></record> |
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subjects | Advertising Algorithms Counterfeit Electronic mail Spamming |
title | Bio inspired email spam detection: A quantitative investigation |
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