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Abualkibash, Munther
- Intrusion Detection System Classification using Different Machine Learning Algorithms on KDD-99 and NSL-KDD Datasets
Abstract Views :194 |
PDF Views:255
Authors
Affiliations
1 Department of Computer Science, Eastern Michigan University, Ypsilanti, Michigan, US
2 School of Information Security and Applied Computing, Eastern Michigan University, Ypsilanti, Michigan, US
1 Department of Computer Science, Eastern Michigan University, Ypsilanti, Michigan, US
2 School of Information Security and Applied Computing, Eastern Michigan University, Ypsilanti, Michigan, US
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 11, No 3 (2019), Pagination: 65-80Abstract
Intrusion Detection System (IDS) has been an effective way to achieve higher security in detecting malicious activities for the past couple of years. Anomaly detection is an intrusion detection system. Current anomaly detection is often associated with high false alarm rates and only moderate accuracy and detection rates because it’s unable to detect all types of attacks correctly. An experiment is carried out to evaluate the performance of the different machine learning algorithms using KDD-99 Cup and NSL-KDD datasets. Results show which approach has performed better in term of accuracy, detection rate with reasonable false alarm rate.Keywords
Intrusion Detection System, KDD-99 Cup, NSL-KDD, Machine Learning Algorithms.Full Text
References
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- Analysing Chatgpt’s Potential Through The Lens of Creating Research Papers
Abstract Views :37 |
PDF Views:28
Authors
Affiliations
1 School of Information Security and Applied Computing, Eastern Michigan University, Ypsilanti, Michigan, US
1 School of Information Security and Applied Computing, Eastern Michigan University, Ypsilanti, Michigan, US
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 15, No 4 (2023), Pagination: 49-65Abstract
This paper analyses ChatGPT 3.5 Turbo, the latest free version of the ChatGPT service. By using ChatGPT to create theoretical papers on itself, further insights are gained into the potential of ChatGPT and other generative artificial intelligence services as well as their weaknesses. Through this analysis presented, potential future avenues of research are suggested alongside necessary changes if services like ChatGPT wish to be used as a tool in academic works.Keywords
Artificial Intelligence, Large Learning Model, ChatGPT, Generative AI, Research Paper CreationFull Text
References
- Liu, H., Ren, X., & Wang, Y. (2020). Using Generative Pre-trained Transformer for Academic Abstract Generation. In Proceedings of the 12th International Conference on Educational and Information Technology (EAIT 2020) (pp. 84-91).
- Malik, M. A., Alshamrani, A., &Aljohani, N. R. (2021). ChatGPT-Assisted Essay Writing for ESL/EFL Students. Journal of Educational Computing Research, 59(5), 1235-1261.
- Sharma, R., Lall, B., & Ghosh, S. (2021). GPT-Based Automated Literature Review Generation. In Proceedings of the 2021 3rd International Conference on Advances in Computing, Communication and Information Science (ICACCI) (pp. 155-159). IEEE.