Fedack: Federated adversarial contrastive knowledge distillation for cross-lingual and cross-model social bot detection
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 …
social platforms. The state-of-the-art detection models are siloed and have largely …
Graph mining for cybersecurity: A survey
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 …
caused severe consequences on society. Securing cyberspace has become a great concern …
Unsupervised social bot detection via structural information theory
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 …
of information dissemination while increasing trust in social interactions. The current …
BIC: Twitter bot detection with text-graph interaction and semantic consistency
Twitter bots are automatic programs operated by malicious actors to manipulate public
opinion and spread misinformation. Research efforts have been made to automatically …
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
As malicious actors employ increasingly advanced and widespread bots to disseminate
misinformation and manipulate public opinion, the detection of Twitter bots has become a …
misinformation and manipulate public opinion, the detection of Twitter bots has become a …
Multi-modal social bot detection: Learning homophilic and heterophilic connections adaptively
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 …
media. With social bots evolving continually, they primarily evade detection by imitating …
Heterophily-aware social bot detection with supervised contrastive learning
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 …
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
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 …
information, but they have also led to a proliferation of content not always reliable and …
Twitter bot identification: An anomaly detection approach
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 …
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 …
misinformation and manipulating the public opinion about several issues, ie, elections and …