Abstract
In E-Learning Platforms like LinkedIn, identifying fake profiles poses significant challenges, affecting trust and engagement. Fake Profiles can mislead users, dilute the quality of interactions and undermine the credibility of the Platform. This survey explores the application of machine learning techniques for detecting fake profiles on e-learning platforms. The study examines various features that can indicate suspicious behaviours, such as anomalous login patterns, unusual interaction metrics, and inconsistent profile information. Through a comprehensive review of existing research, the study identifies the key challenges in implementing machine learning solutions for fake profile detection, such as data privacy concerns, feature engineering, and scalability. Additionally, the survey highlights the potential of using machine learning models and ensemble techniques to enhance detection accuracy. By consolidating insights from prior studies, this survey aims to provide a foundation for future research and development in safeguarding e-learning platforms against fake profiles, thereby enhancing a secure and trustworthy digital learning environment.
References
Aditya, Bhrugumalla LVS, and Sachi Nandan Mohanty. "Heterogenous Social Media Analysis for Efficient Deep Learning Fake-Profile Identification." IEEE Access (2023).
Lin, Chen, Si Chen, Meifang Zeng, Sheng Zhang, Min Gao, and Hui Li. "Shilling black-box recommender systems by learning to generate fake user profiles." IEEE Transactions on Neural Networks and Learning Systems 35, no. 1 (2022): 1305-1319.
Roy, Pradeep Kumar, and Shivam Chahar. "Fake profile detection on social networking websites: a comprehensive review." IEEE Transactions on Artificial Intelligence 1, no. 3 (2020): 271-285.
Masood, Faiza, Ahmad Almogren, Assad Abbas, Hasan Ali Khattak, Ikram Ud Din, Mohsen Guizani, and Mansour Zuair. "Spammer detection and fake user identification on social networks." IEEE Access 7 (2019): 68140-68152.
Lingam, Greeshma, Rashmi Ranjan Rout, Durvasula VLN Somayajulu, and Soumya K. Ghosh. "Particle swarm optimization on deep reinforcement learning for detecting social spam bots and spam-influential users in twitter network." IEEE Systems Journal 15, no. 2 (2020): 2281-2292.
Amira, Abdelouahab, Abdelouahid Derhab, Samir Hadjar, Mustapha Merazka, Md Golam Rabiul Alam, and Mohammad Mehedi Hassan. "Detection and analysis of fake news users’ communities in social media." IEEE Transactions on Computational Social Systems (2023).
Zhang, Xuxin, Jian Chen, Rui Zhang, Chen Wang, and Ling Liu. "Attacking recommender systems with plausible profile." IEEE Transactions on Information Forensics and Security 16 (2021): 4788-4800.
Hu, Shigang, Akshi Kumar, Fadi Al-Turjman, Shivam Gupta, and Simran Seth. "Reviewer credibility and sentiment analysis based user profile modelling for online product recommendation." Ieee Access 8 (2020): 26172-26189.
-Althaqafi, Nahid R., Hessah A. Alsalamah, and Walaa N. Ismail. "The Impact of the Weighted Features on the Accuracy of X-Platform’s User Credibility Detection Using Supervised Machine Learning." IEEE Access (2024).
Kanwal, Moona, Najeed A. Khan, Najma Ismat, Aftab A. Khan, and Muzammil Ahmad Khan. "Machine Learning Approach to Classification of Online Users by Exploiting Information Seeking Behavior." IEEE Access (2024).
Sansonetti, Giuseppe, Fabio Gasparetti, Giuseppe D’aniello, and Alessandro Micarelli. "Unreliable users detection in social media: Deep learning techniques for automatic detection." IEEE Access 8 (2020): 213154-213167.
Felouat, Hichem, Huy H. Nguyen, Trung-Nghia Le, Junichi Yamagishi, and Isao Echizen. "eKYC-DF: A Large-Scale Deepfake Dataset for Developing and Evaluating eKYC Systems." IEEE Access (2024).
Aguilera, Ana, Pamela Quinteros, Irvin Dongo, and Yudith Cardinale. "CrediBot: Applying Bot Detection for Credibility Analysis on Twitter." IEEE Access (2023).
Van Der Walt, Estée, and Jan Eloff. "Using machine learning to detect fake identities: bots vs humans." IEEE access 6 (2018): 6540-6549.
Kausar, Soufia, Bilal Tahir, and Muhammad Amir Mehmood. "Push-to-trend: A novel framework to detect trend promoters in trending hashtags." IEEE Access 10 (2022): 113005-113017.
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