Survey Paper on Automatic Detection of Fake Profile Using Machine Learning on Instagram
-
Published:2021-05-07
Issue:
Volume:
Page:46-50
-
ISSN:2394-4099
-
Container-title:International Journal of Scientific Research in Science, Engineering and Technology
-
language:en
-
Short-container-title:IJSRSET
Author:
Meshram Er. Pranay1, Bhambulkar Rutika2, Pokale Puja2, Kharbikar Komal2, Awachat Anushree2
Affiliation:
1. Assistant Professor, Department of Computer Science and Engineering, Priyadarshini J. L. College of Engineering, Nagpur, Maharashtra, India 2. BE Scholar, Department of Computer Science and Engineering, Priyadarshini J. L. College of Engineering, Nagpur, Maharashtra, India
Abstract
With the arrival of the Internet and social media, at the same time as masses of humans have benefitted from the full-size reassets of records available, there was an full-size boom with inside the upward push of cyber-crimes, mainly targeted closer to women. According to a 2019 file with inside the Economics Times, India has witnessed a 457% upward push in cybercrime with inside the 5 years span among 2011 and 2016. Most speculate that that is because of effect of social media inclusive of Facebook, Instagram and Twitter on our day by day lives. While those simply assist in growing a legitimate social network, advent of consumer debts in those websites normally desires simply an email-id. A actual lifestyles man or woman can create more than one fake IDs and for this reason impostors can effortlessly be made. Unlike the actual international state of affairs in which more than one policies and guidelines are imposed to become aware of oneself in a completely unique manner (as an instance at the same time as issuing one’s passport or driver’s license), with inside the digital international of social media, admission does now no longer require this kind of checks. In this paper, we study the one-of-a-kind debts of Instagram, specifically and try and verify an account as fake or actual the use of Machine Learning strategies specifically Logistic Regression and Random Forest Algorithm.
Publisher
Technoscience Academy
Reference10 articles.
1. Guo, G., Zhu, Y., Yu, R., Chu, W.C.C., Ma, D. (2020). A privacy-preserving framework with self- governance and permission delegation in online social networks.IEEE Access,8:157116-157129. https://doi.org/10.1109/ACCESS.2020.3016041 2. Boididou, C., Middleton, S.E., Jin, Z., Papadopoulos, S., Dang-Nguyen, D.T., Boato, G., Kompatsiaris, Y. (2018). Verifying information with multimedia content on twitter. Multimedia Tools and Applications, 77(12): 15545-15571. https://doi.org/10.1007/s11042-017-5132-9 3. Alqatawna, J., Madain, A., Al-Zoubi, A., Al-Sayyed,R. (2017). Online social networks security: Threats, attacks, and future directions. In Social Media Shaping ePublishing and Academia,pp.121132. https://doi.org/10.1007/978-3-319-55354-210 4. Lorincz, L., Koltai, J., Gy?r, A.F., Takacs, K. (2019). Collapse of an online social network: Burning social capital to create it? Social Networks,57:43-53. https://doi.org/10.1016/j.socnet.2018.11.004 5. Arora, A., Bansal, S., Kandpal, C., Aswani, R., Dwivedi, Y. (2019). Measuring social media influencer index-insights from Facebook, Twitter and Instagram. Journal Of Retailing and Consumer Services, 49: 86-101. https://doi.org/10.1016/j.jretconser.2019.03.012
|
|