AIRCC's International Journal of Computer Science and Information Technology

Open Access Open Access  Restricted Access Subscription Access

Detection of Fake Accounts in Instagram using Machine Learning


Affiliations
1 National Institute of Technology, Tiruchirappalli, India
2 PES University, Bangalore, India
3 RV College of Engineering, Bangalore, India
4 Manipal Institute of Technology, Karnataka, India
 

With the advent of the Internet and social media, while hundreds of people have benefitted from the vast sources of information available, there has been an enormous increase in the rise of cyber-crimes, particularly targeted towards women. According to a 2019 report in the [4] Economics Times, India has witnessed a 457% rise in cybercrime in the five year span between 2011 and 2016. Most speculate that this is due to impact of social media such as Facebook, Instagram and Twitter on our daily lives. While these definitely help in creating a sound social network, creation of user accounts in these sites usually needs just an email-id. A real life person can create multiple fake IDs and hence impostors can easily be made. Unlike the real world scenario where multiple rules and regulations are imposed to identify oneself in a unique manner (for example while issuing one’s passport or driver’s license), in the virtual world of social media, admission does not require any such checks. In this paper, we study the different accounts of Instagram, in particular and try to assess an account as fake or real using Machine Learning techniques namely Logistic Regression and Random Forest Algorithm.

Keywords

Logistic Regression, Random Forest Algorithm, Median Imputation, Maximum Likelihood Estimation, K Cross Validation, Overfitting, Out of Bag Data, Recall, Identity Theft, Angler Phishing.
User
Notifications
Font Size

  • Indira Sen,Anupama Aggarwal,Shiven Mian.2018."Worth its Weight in Likes: Towards Detecting Fake Likes on Instagram". In ACM International Conference on Information and Knowledge Management.

  • Shalinda Adikari, Kaushik Dutta. 2014. “Identifying Fake Profiles In LinkedIn”. In Pacific Asia Conference on Information Systems.

  • Aleksei Romanov, Alexander Semenov, Oleksiy Mazhelis and Jari Veijalainen.2017. "Detection of Fake Profiles in Social Media”. In 13th International Conference on Web Information Systems and Technologies.

  • https://telecom.economictimes.indiatimes.com/news/india-saw-457-rise-in-cybercrime-in-fiveyears-study/67455224

  • Todor Mihaylov, Preslav Nakov.2016. "Hunting for Troll Comments in News Community Forums". In Association for Computational Linguistics.

  • Ml-cheatsheet.readthedocs.io. (2019). Logistic Regression — ML Cheatsheet documentation. [Online] Available at: https://ml cheatsheet.readthedocs.io/en/latest/logistic_regression.html#binarylogistic-regression [Accessed 10 Jun. 2019].

  • 3. Schoonjans, F. (2019). ROC curve analysis with MedCalc. [Online] MedCalc. Available at: https://www.medcalc.org/manual/roc-curves.php [Accessed 10 Jun. 2019].

  • Kietzmann, J.H., Hermkens, K., McCarthy, I.P., Silvestre,B.S., 2011. Social media? Get serious! Understanding the functional building blocks of social media. Bus.Horiz., SPECIAL ISSUE: SOCIAL MEDIA 54, 241251. doi:10.1016/j.bushor.2011.01.005.

  • Krombholz, K., Hobel, H., Huber, M., Weippl, E., 2015.Advanced Social Engineering Attacks. J Inf SecurAppl 22, 113–122. doi:10.1016/j.jisa.2014.09.005.


Abstract Views: 522

PDF Views: 249




  • Detection of Fake Accounts in Instagram using Machine Learning

Abstract Views: 522  |  PDF Views: 249

Authors

Ananya Dey
National Institute of Technology, Tiruchirappalli, India
Hamsashree Reddy
PES University, Bangalore, India
Manjistha Dey
RV College of Engineering, Bangalore, India
Niharika Sinha
Manipal Institute of Technology, Karnataka, India

Abstract


With the advent of the Internet and social media, while hundreds of people have benefitted from the vast sources of information available, there has been an enormous increase in the rise of cyber-crimes, particularly targeted towards women. According to a 2019 report in the [4] Economics Times, India has witnessed a 457% rise in cybercrime in the five year span between 2011 and 2016. Most speculate that this is due to impact of social media such as Facebook, Instagram and Twitter on our daily lives. While these definitely help in creating a sound social network, creation of user accounts in these sites usually needs just an email-id. A real life person can create multiple fake IDs and hence impostors can easily be made. Unlike the real world scenario where multiple rules and regulations are imposed to identify oneself in a unique manner (for example while issuing one’s passport or driver’s license), in the virtual world of social media, admission does not require any such checks. In this paper, we study the different accounts of Instagram, in particular and try to assess an account as fake or real using Machine Learning techniques namely Logistic Regression and Random Forest Algorithm.

Keywords


Logistic Regression, Random Forest Algorithm, Median Imputation, Maximum Likelihood Estimation, K Cross Validation, Overfitting, Out of Bag Data, Recall, Identity Theft, Angler Phishing.

References