Open Access
| Issue |
E3S Web Conf.
Volume 430, 2023
15th International Conference on Materials Processing and Characterization (ICMPC 2023)
|
|
|---|---|---|
| Article Number | 01070 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/e3sconf/202343001070 | |
| Published online | 06 October 2023 | |
- AshwiniKatkar, SakshiShukla, Danish Shaikh, PradipDange, Malware Intrusion Detection For System Security, International Conference on Communication information and Computing Technology (ICCICT), (2021) [Google Scholar]
- A Abdul Rasheed, Vulnerability detection towards protecting intrusion by Social Network Analysis approach, 5th International Conference on Trends in Electronics and Informatics (ICOEI), (2021) [Google Scholar]
- SibiAmaran, R. Madhan Mohan, Intrusion Detection System using Optimal Support Vector Machine for Wireless Sensor Networks, International Conference on Artificial Intelligence and Smart Systems (ICAIS), (2021) [Google Scholar]
- Yaofu Cao, Xiaomeng Li, Shulin Zhang, Yang Li, Liang Chen, Yunrui He, Design of network security situation awareness analysis module for electric power dispatching and control system, 2nd International Conference on Information Technology and Computer Application (ITCA), (2020) [Google Scholar]
- S. Prabhu, Mary Anita E.A., Trust based secure routing mechanisms for wireless sensor networks: A survey, 6th International Conference on Advanced Computing and Communication Systems (ICACCS), (2020) [Google Scholar]
- Zhaoyue Wu, Hongjun Su, Qian Du, Low-Rank and Collaborative Representation for Hyperspectral Anomaly Detection, IGARSS 2019 - IEEE International Geoscience and Remote Sensing Symposium, (2019) [Google Scholar]
- Dimitrios Papamartzivanos, Félix Gómez Mármol, GeorgiosKambourakis, IEEE Access . 7, (2019) [Google Scholar]
- P. V. Haripriya, J. S. Anju, An AIS based anomaly detection system, International Conference on Computing Methodologies and Communication (ICCMC), (2017) [Google Scholar]
- Rohini Rajpal, Sanmeet Kaur, Raman deep Kaur, Improving detection rate using misuse detection and machine learning, SAI Computing Conference (SAI), (2016) [Google Scholar]
- Tahir Mehmood, Helmi B. MdRais, Machine learning algorithms in context of intrusion detection, 3rd International Conference on Computer and Information Sciences (ICCOINS), (2016) [Google Scholar]
- Praneeth Nskh, M Naveen Varma, Roshan Ramakrishna Naik, Principle component analysis based intrusion detection system using support vector machine “, IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), (2016) [Google Scholar]
- Yogita Danane, Thaksen Parvat, “Intrusion detection system using fuzzy genetic algorithm “, International Conference on Pervasive Computing (ICPC), (2015) [Google Scholar]
- Nagaraja, A., Boregowda, U., Khatatneh, K., Vangipuram, R., Nuvvusetty, R., Sravan Kiran, V., IEEE Access, 8, art. no. 9006824, pp. 39184-39196. (2020) [CrossRef] [Google Scholar]
- Pradeep, G., Sakthidharan, G.R, A Survey on Performance Comparison of Support Vector Machine, Random Forest, and Extreme Learning Machine for Intrusion Detection, International Conference On Machine Learning Big Data Management Cloud and Computing, (2021) [Google Scholar]
- Sri Vidya, M., Sakthidharan, G.R., Accurate Anomaly Detection using various Machine Learning methods for IoT devices in Indoor Environment, Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC (2021) [Google Scholar]
- Shalli Rani, M. Balasaraswathi, P. Chandra Sekhar Reddy, Gurbinder Singh Brar, M. Sivaram & Vigneswaran Dhasarathan, Wireless Networks, 26, (2020) [Google Scholar]
- P Chandra Sekhar Reddy, G. R. Sakthidharan, International Journal of Intelligent Engineering and Systems, 12, (2019) [Google Scholar]
- N. Madhusudhana Reddy, G. Ramesh, Srinivasa Babu Kasturi, D. Sharmila, G. Gopichand & L. Thomas Robinson, Applied Nanoscience, 13, (2023). [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.