Social Networking Security during COVID‐19: A Systematic Literature Review
During the Covid‐19 Pandemic, the usage of social media networks increased
exponentially. People engage in education, business, shopping, and other social activities …
exponentially. People engage in education, business, shopping, and other social activities …
Mush: Multi-stimuli hawkes process based sybil attacker detector for user-review social networks
User-Review Social Networks (URSNs) now become the targets of Sybil attacks, where fake
reviews are posted by attackers to raise the reputation of listed services or products. Unlike …
reviews are posted by attackers to raise the reputation of listed services or products. Unlike …
[PDF][PDF] Exploring machine learning techniques for fake profile detection in online social networks
NSG Bharti, P Gulia - Int. J. Electr. Comput. Eng. IJECE, 2023 - researchgate.net
The online social network is the largest network, more than 4 billion users use social media
and with its rapid growth, the risk of maintaining the integrity of data has tremendously …
and with its rapid growth, the risk of maintaining the integrity of data has tremendously …
Active malicious accounts detection with multimodal fusion machine learning algorithm
This paper presents a multi-modal fusion machine learning algorithm to detect active
malicious accounts in social networks. First, we use the XGBoost algorithm to rank features' …
malicious accounts in social networks. First, we use the XGBoost algorithm to rank features' …
Detecting fake reviews with generative adversarial networks for mobile social networks
With the growth of mobile social networks (MSNs), crowdsourced information could be used
for recommendation to mobile users. However, it is quite vulnerable to Sybil attacks, where …
for recommendation to mobile users. However, it is quite vulnerable to Sybil attacks, where …
Uncovering Malicious Accounts in Online Social Networks Using XGBoost and Graph Convolution Networks
Y Tang, D Zhang, KC Li, J Yuan - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In this work, we introduce a Machine-Learning (ML) approach based on XGBoost and Graph
Convolutional Networks (GCNs) for the detection of active malicious accounts in Online …
Convolutional Networks (GCNs) for the detection of active malicious accounts in Online …