A categorization scheme for socialbot attacks in online social networks
Silvia Mitter, Claudia Wagner, Markus Strohmaier

TL;DR
This paper proposes a comprehensive categorization scheme for socialbot attacks in online social networks to better understand and characterize these threats, aiding in the development of more effective defenses.
Contribution
It introduces a novel categorization framework for socialbot attacks and demonstrates its application to recent attack cases, advancing the understanding of attack techniques.
Findings
The categorization scheme effectively classifies recent socialbot attacks.
It provides a structured overview of attack techniques in OSNs.
The scheme aids in identifying patterns and trends in socialbot attacks.
Abstract
In the past, online social networks (OSN) like Facebook and Twitter became powerful instruments for communication and networking. Unfortunately, they have also become a welcome target for socialbot attacks. Therefore, a deep understanding of the nature of such attacks is important to protect the Eco-System of OSNs. In this extended abstract we propose a categorization scheme of social bot attacks that aims at providing an overview of the state of the art of techniques in this emerging field. Finally, we demonstrate the usefulness of our categorization scheme by characterizing recent socialbot attacks according to our categorization scheme.
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Taxonomy
TopicsSpam and Phishing Detection · Network Security and Intrusion Detection · Advanced Malware Detection Techniques
