## 4 Results
### Results of Keyword Frequency (TF-IDF) Analysis  
A term frequency-inverse document frequency (TF-IDF) analysis was performed to evaluate the significance of key terms in the GAI security research corpus. This analysis provides insights into the most frequently occurring words, as well as those with unique significance, as indicated by their TF-IDF scores in Table 2.  
The term \"ChatGPT\" emerged as the most frequent word, appearing 2799 times across the documents. However, its TF-IDF score of 602 is relatively moderate. This suggests that while \"ChatGPT\" is commonly mentioned, its occurrence is spread across multiple \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Rank** & **Word** & **Frequency** & **Word** & **TF-IDF** & **Rank** & **Word** & **Frequency** & **Word** & **TF-IDF** \\ \hline
1 & ChatGPT & 2799.00 & model & 602 & \(11\) & education & 499 & analysis & 297 \\
2 & model & 1503.00 & language & 530 & \(12\) & intelligence & 472 & use & 294 \\
3 & AI & 1271.00 & AI & 433 & \(13\) & system & 466 & security & 265 \\
4 & language & 958 & datum & 408 & 14 & result & 464 & development & 256 \\
5 & datum & 768 & intelligence & 367 & \(15\) & use & 454 & information & 250 \\
6 & LLM & 735 & technology & 360 & \(16\) & challenge & 453 & system & 239 \\
7 & technology & 684 & result & 348 & \(17\) & analysis & 449 & finding & 237 \\
8 & tool & 611 & application & 334 & \(18\) & security & 432 & method & 236 \\
9 & application & 552 & tool & 331 & \(19\) & user & 420 & task & 232 \\
10 & student & 544 & challenge & 307 & \(20\) & information & 403 & education & 231 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Keyword frequency and TF-IDF scores in GAI security research. Figure 6: Distribution of research publications by institution. documents, thus diminishing its contribution to the uniqueness of any individual document. Consequently, this term is central to the overall research landscape, but it may not be the defining focus of specific studies. In contrast, the term \"model\" appears 1503 times and has a high TF-IDF score of 602, highlighting its importance both in terms of frequency and its distinct presence in certain documents. This likely reflects discussions on GAI models and their implications for security. Similarly, \"AI\" (artificial intelligence) is mentioned 1271 times, with a notable TF-IDF score of 433, emphasizing its pivotal role in research centered on generative AI. Other prominent terms include \"language\", \"data\", and \"intelligence\", which rank highly in both frequency and TF-IDF scores. For example, the term \"language\" appears 958 times, with a TF-IDF score of 530, underscoring its critical importance in discussions of large language models (LLMs), a key component of GAI research. The terms \"data\" (TF-IDF: 408) and \"intelligence\" (TF-IDF: 367) are also central to analyses of information systems and intelligence frameworks--crucial aspects in the application of GAI to security challenges. Terms such as \"technology\", \"tool\", and \"application\" also exhibit moderate-to-high TF-IDF scores, signaling their relevance in discussions about the practical implementation of GAI technologies across various domains. These words reflect the growing interest in how GAI can be operationalized for specific use cases, particularly in areas like security and technology management. Additionally, terms such as \"challenge\" (TF-IDF: 307) and \"analysis\" (TF-IDF: 297) suggest ongoing discussions about the challenges and methodological considerations in integrating GAI into existing security frameworks. These words highlight the practical obstacles and strategic analysis required for the effective deployment of GAI technologies in sensitive environments. Finally, terms related to \"security\" (TF-IDF: 265) and \"information\" (TF-IDF: 250) are central to the discourse, reflecting the research focus on securing data and systems in the context of GAI applications.