Chat-GPT for Android malware detection
The use of large-language models (LLMs) in the field of cybersecurity has been increasing greatly in recent years. With the advent of ChatGPT by OpenAI, there have been many different use cases for LLMs in cybersecurity, including in intrusion detection, as well as in vulnerability detection. Howeve...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/175132 |
| _version_ | 1811683379381272576 |
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| author | Ong, Eliezer De Zhi |
| author2 | Liu Yang |
| author_facet | Liu Yang Ong, Eliezer De Zhi |
| author_sort | Ong, Eliezer De Zhi |
| collection | NTU |
| description | The use of large-language models (LLMs) in the field of cybersecurity has been increasing greatly in recent years. With the advent of ChatGPT by OpenAI, there have been many different use cases for LLMs in cybersecurity, including in intrusion detection, as well as in vulnerability detection. However, there has yet to be much research done in the use of LLMs for malware detection, more specifically, in the area of Android malware detection. In this paper, we will look at how we can capitalise on the use of ChatGPT in detecting malware or malicious source code in Android applications. We will devise various prompts and include a framework design that will allow ChatGPT to detect Android malware code. We will also propose a hierarchical structure to evaluate the effectiveness of ChatGPT in Android malware detection. This hierarchical structure aims to understand the important pieces of information which are present in malware applications, that are needed by ChatGPT to detect malicious pieces of code in Android applications. In the study, we found that the manifest files are sufficient for ChatGPT to detect malicious code in 68% of a specific malware family. Through this study, we will be able to understand how ChatGPT is able to detect malware and understand the reasons for failing to detect. |
| first_indexed | 2024-10-01T04:11:48Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/175132 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:11:48Z |
| publishDate | 2024 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1751322024-04-26T15:40:47Z Chat-GPT for Android malware detection Ong, Eliezer De Zhi Liu Yang School of Computer Science and Engineering yangliu@ntu.edu.sg Computer and Information Science The use of large-language models (LLMs) in the field of cybersecurity has been increasing greatly in recent years. With the advent of ChatGPT by OpenAI, there have been many different use cases for LLMs in cybersecurity, including in intrusion detection, as well as in vulnerability detection. However, there has yet to be much research done in the use of LLMs for malware detection, more specifically, in the area of Android malware detection. In this paper, we will look at how we can capitalise on the use of ChatGPT in detecting malware or malicious source code in Android applications. We will devise various prompts and include a framework design that will allow ChatGPT to detect Android malware code. We will also propose a hierarchical structure to evaluate the effectiveness of ChatGPT in Android malware detection. This hierarchical structure aims to understand the important pieces of information which are present in malware applications, that are needed by ChatGPT to detect malicious pieces of code in Android applications. In the study, we found that the manifest files are sufficient for ChatGPT to detect malicious code in 68% of a specific malware family. Through this study, we will be able to understand how ChatGPT is able to detect malware and understand the reasons for failing to detect. Bachelor's degree 2024-04-22T02:42:17Z 2024-04-22T02:42:17Z 2024 Final Year Project (FYP) Ong, E. D. Z. (2024). Chat-GPT for Android malware detection. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175132 https://hdl.handle.net/10356/175132 en application/pdf Nanyang Technological University |
| spellingShingle | Computer and Information Science Ong, Eliezer De Zhi Chat-GPT for Android malware detection |
| title | Chat-GPT for Android malware detection |
| title_full | Chat-GPT for Android malware detection |
| title_fullStr | Chat-GPT for Android malware detection |
| title_full_unstemmed | Chat-GPT for Android malware detection |
| title_short | Chat-GPT for Android malware detection |
| title_sort | chat gpt for android malware detection |
| topic | Computer and Information Science |
| url | https://hdl.handle.net/10356/175132 |
| work_keys_str_mv | AT ongeliezerdezhi chatgptforandroidmalwaredetection |