A novel machine learning-based framework for detecting fake Instagram profiles

被引:4
|
作者
Kaushik, Keshav [1 ]
Bhardwaj, Akashdeep [1 ]
Kumar, Manoj [2 ]
Gupta, Sachin Kumar [3 ]
Gupta, Abhishek [4 ]
机构
[1] Univ Petr & Energy Studies, Sch Comp Sci, Dehra Dun, Uttarakhand, India
[2] Univ Wollongong Dubai, Fac Engn & Informat Sci, Dubai Knowledge Pk, Dubai, U Arab Emirates
[3] Shri Mata Vaishno Devi Univ, Sch Elect & Commun Engn, Katra, India
[4] Shri Mata Vaishno Devi Univ, Sch Comp Sci & Engn, Katra, Jammu & Kashmir, India
来源
关键词
cyberattacks; deep neural model; detection methods; fake identity; fake profile; Instagram; machine learning; phishing;
D O I
10.1002/cpe.7349
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Recently, there has been a massive rise in the popularity of Instagram, which connects individuals globally and allows videos and images to be uploaded and exchanged, and communicated over social media. Instagram is also an online playground of deceit. The use of filters, lighting, and cunning angles transforms the mundane into something spectacular. Automated spam accounts and fake profiles use this to their malicious advantage for executing attacks targeting high-profile executives. Creating fake Instagram identities is easy to reproduce the idea of being accepted by many fans on social media. Fake accounts are used in the marketing of fake services and products. This research focused on designing and training a unique neural network model and proposed a new algorithm for detecting automated spam and fake Instagram account profiles. The precision and accuracy of the proposed method were achieved at 93% and 91%, respectively.
引用
收藏
页数:12
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