# Leveraging Dialogue State Tracking for Zero-Shot Chat-Based Social Engineering Attack Recognition
## 7 Conclusions  
The aim of this study was to investigate schema-guided dialogue-state tracking in the context of CSE attacks. We created a set of fourteen dialogue acts and developed the SG-CSE Corpus using the CSE ontology and corpus. We followed the schema-guided paradigm to introduce the SG-CSE BERT, a simplistic model for zero-shot CSE attack state tracking. The performance results were promising and demonstrated the effectiveness of the approach. To provide context for the study, we discussed dialogue systems and their characteristics, which helped us define our approach. Then, we examined how concepts and terminology from task-based dialogue systems and dialogue-state tracking can be transferred to the CSE attack domain.  
We focused on creating the SG-CSE DAs and SG-CSE Corpus, mapping slots and intents, and proposing the SG-CSE BERT model. The model achieved satisfactory performance results using a small model and input encoding. Although various model enhancements were attempted, no significant improvement was observed. The study suggests that data augmentation and the addition of hand-crafted features could improve the performance of the CSE attack state tracking, but further experimentation is necessary to explore these methods. The proposed model offers an advantage in the few-shot experiments, where only limited labeled data is available. Such an approach can help to create a more comprehensive and accurate understanding of CSE attacks and their underlying mechanisms, as well as to develop more effective detection and prevention strategies. For example, experts in natural language processing can help to improve the performance of dialogue-state tracking models, while experts in psychology and sociology can provide insights into the social engineering tactics used in CSE attacks and the psychological factors that make users susceptible to these attacks. Cyber-security experts can provide a deeper understanding of the technical aspects of CSE attacks and help to develop more robust and effective defense mechanisms.  
In addition, it is important to emphasize the need for ethical considerations in the development of CSE attack detection systems. As these systems involve the processing of sensitive and personal information, it is crucial to ensure that they are designed and used in a way that respects privacy and protects against potential biases and discrimination. This requires a careful and transparent design process, as well as ongoing monitoring and evaluation of the system's performance and impact. Overall, a multi-disciplinary and ethical approach is essential for the development of effective and responsible CSE attack detection systems.  
Future works will focus on the SG-CSE corpus augmentation techniques to present new CSE attack services. Furthermore, the proposed SG-CSE BERT will be incorporated into an ensemble system that will detect CSE attacks, where it will act as an individual component responsible for practicing dialogue-state tracking.  
Conceptualization, N.T., P.F. and I.M.; methodology, N.T. and I.M.; software, N.T.; evaluation, N.T. and P.F.; writing--original draft preparation, N.T. and P.F.; writing--review and editing, N.T., P.F. and I.M. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.