Fedack: Federated adversarial contrastive knowledge distillation for cross-lingual and cross-model social bot detection

Y Yang, R Yang, H Peng, Y Li, T Li, Y Liao… - Proceedings of the ACM …, 2023 - dl.acm.org
Social bot detection is of paramount importance to the resilience and security of online
social platforms. The state-of-the-art detection models are siloed and have largely …

Graph mining for cybersecurity: A survey

B Yan, C Yang, C Shi, Y Fang, Q Li, Y Ye… - ACM Transactions on …, 2023 - dl.acm.org
The explosive growth of cyber attacks today, such as malware, spam, and intrusions, has
caused severe consequences on society. Securing cyberspace has become a great concern …

Unsupervised social bot detection via structural information theory

H Peng, J Zhang, X Huang, Z Hao, A Li, Z Yu… - arXiv preprint arXiv …, 2024 - arxiv.org
Research on social bot detection plays a crucial role in maintaining the order and reliability
of information dissemination while increasing trust in social interactions. The current …

BIC: Twitter bot detection with text-graph interaction and semantic consistency

Z Lei, H Wan, W Zhang, S Feng, Z Chen, J Li… - arXiv preprint arXiv …, 2022 - arxiv.org
Twitter bots are automatic programs operated by malicious actors to manipulate public
opinion and spread misinformation. Research efforts have been made to automatically …

LMbot: distilling graph knowledge into language model for graph-less deployment in twitter bot detection

Z Cai, Z Tan, Z Lei, Z Zhu, H Wang, Q Zheng… - Proceedings of the 17th …, 2024 - dl.acm.org
As malicious actors employ increasingly advanced and widespread bots to disseminate
misinformation and manipulate public opinion, the detection of Twitter bots has become a …

Multi-modal social bot detection: Learning homophilic and heterophilic connections adaptively

S Li, B Qiao, K Li, Q Lu, M Lin, W Zhou - Proceedings of the 31st ACM …, 2023 - dl.acm.org
The detection of social bots has become a critical task in maintaining the integrity of social
media. With social bots evolving continually, they primarily evade detection by imitating …

Heterophily-aware social bot detection with supervised contrastive learning

Q Wu, Y Yang, B He, H Liu, X Wang, Y Liao… - arXiv preprint arXiv …, 2023 - arxiv.org
Detecting ever-evolving social bots has become increasingly challenging. Advanced bots
tend to interact more with humans as a camouflage to evade detection. While graph-based …

From online behaviours to images: A novel approach to social bot detection

E Di Paolo, M Petrocchi, A Spognardi - International Conference on …, 2023 - Springer
Abstract Online Social Networks have revolutionized how we consume and share
information, but they have also led to a proliferation of content not always reliable and …

Twitter bot identification: An anomaly detection approach

L Alkulaib, L Zhang, Y Sun… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
The vast presence of bots on Twitter requires reliable and accurate bot detection methods
that differentiate legitimate bots from malicious ones. Despite the success of those methods …

Multimodal Detection of Social Spambots in Twitter using Transformers

L Ilias, IM Kazelidis, D Askounis - arXiv preprint arXiv:2308.14484, 2023 - arxiv.org
Although not all bots are malicious, the vast majority of them are responsible for spreading
misinformation and manipulating the public opinion about several issues, ie, elections and …