Naman Singh, Tushar Sharma, Abha Thakral, T. Choudhury
{"title":"Detection of Fake Profile in Online Social Networks Using Machine Learning","authors":"Naman Singh, Tushar Sharma, Abha Thakral, T. Choudhury","doi":"10.1109/ICACCE.2018.8441713","DOIUrl":null,"url":null,"abstract":"In today's world, the social media platforms are being used on daily basis and has become an important part of our lives. The number of peoples on social media platforms are incrementing at a greater level for malicious use. There are numerous cases where produced accounts have been effectively distinguished utilizing machine adapting techniques however the amount of research work is very low to recognize counterfeit characters made by people. For bots the ML models used various features to calculate the no. of followers to the no. of friends that an account has on social media platforms (SOCIAL MEDIA PLATFORMSs). The no. of friends to the no. of followers of any account are easily available in the account profiles and no rights are violated of any accounts. In order to accomplish the task of detecting, identifying and eliminate the fake accounts we establish a forged human account.","PeriodicalId":214619,"journal":{"name":"2018 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Advances in Computing and Communication Engineering (ICACCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACCE.2018.8441713","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 31
Abstract
In today's world, the social media platforms are being used on daily basis and has become an important part of our lives. The number of peoples on social media platforms are incrementing at a greater level for malicious use. There are numerous cases where produced accounts have been effectively distinguished utilizing machine adapting techniques however the amount of research work is very low to recognize counterfeit characters made by people. For bots the ML models used various features to calculate the no. of followers to the no. of friends that an account has on social media platforms (SOCIAL MEDIA PLATFORMSs). The no. of friends to the no. of followers of any account are easily available in the account profiles and no rights are violated of any accounts. In order to accomplish the task of detecting, identifying and eliminate the fake accounts we establish a forged human account.
在当今世界,社交媒体平台每天都在使用,已经成为我们生活的重要组成部分。社交媒体平台上恶意使用的人数正在不断增加。在许多情况下,利用机器适应技术有效地区分了生产的帐户,但是识别人为伪造的字符的研究工作非常少。对于机器人,机器学习模型使用各种特征来计算no。的追随者。一个账户在社交媒体平台(social media platforms)上的好友数量。没有。朋友到不了。任何帐户的追随者都很容易在帐户配置文件中获得,任何帐户都没有权利受到侵犯。为了完成检测、识别和消除虚假账户的任务,我们建立了一个伪造的人工账户。