Open Access
Issue |
E3S Web Conf.
Volume 491, 2024
International Conference on Environmental Development Using Computer Science (ICECS’24)
|
|
---|---|---|
Article Number | 02025 | |
Number of page(s) | 16 | |
Section | Smart Systems for Environmental Development | |
DOI | https://doi.org/10.1051/e3sconf/202449102025 | |
Published online | 21 February 2024 |
- A. Y. Al Hammadi, C. YeobYeun and E. Damiani, “Novel EEG Risk Framework to Identify Insider Threats in National Critical Infrastructure Using Deep Learning Techniques,” 2020 IEEE International Conference on Services Computing (SCC), Beijing, China, 2020, pp. 469-471, doi: 10.1109/SCC49832.2020.00071. [Google Scholar]
- F. Abdel-Fattah, F. AlTamimi and K. A. Farhan, “Machine Learning and Data Mining in Cybersecurty,” 2021 International Conference on Information Technology (ICIT), Amman, Jordan, 2021, pp. 952-956, doi: 10.1109/ICIT52682.2021.9491749. [Google Scholar]
- M. Jutras, E. Liang, S. Leary, C. Ward and K. Manville, “Detecting Physical Adversarial Patch Attacks with Object Detectors,” 2022 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), DC, USA, 2022, pp. 1-7, doi: 10.1109/AIPR57179.2022.10092200. [Google Scholar]
- K. Touloumis, A. Michalitsi-Psarrou, A. Georgiadou and D. Askounis, “A tool for assisting in the forensic investigation of cyber-security incidents,” 2022 IEEE International Conference on Big Data (Big Data), Osaka, Japan, 2022, pp. 2630-2636, doi: 10.1109/BigData55660.2022.10020208. [Google Scholar]
- J. Ali, “Intrusion Detection Systems Trends to Counteract Growing Cyber-Attacks on Cyber-Physical Systems,” 2021 22nd International Arab Conference on Information Technology (ACIT), Muscat, Oman, 2021, pp. 1-6, doi:10.1109/ACIT53391.2021.9677429. [Google Scholar]
- Y. K. Saheed and M. O. Arowolo, “Efficient Cyber Attack Detection on the Internet of Medical Things-Smart Environment Based on Deep Recurrent Neural Network and Machine Learning Algorithms,” in IEEE Access, vol. 9, pp. 161546-161554, 2021, doi: 10.1109/ACCESS.2021.3128837. [CrossRef] [Google Scholar]
- S. Ajani and M. Wanjari, “An Efficient Approach for Clustering Uncertain Data Mining Based on Hash Indexing and Voronoi Clustering,” 2013 5th International Conference and Computational Intelligence and Communication Networks, 2013, pp. 486-490, doi: 10.1109/CICN.2013.106. [Google Scholar]
- Khetani, V.. , Gandhi, Y.. , Bhattacharya, S.. , Ajani, S. N. ., &Limkar, S.. (2023). Cross-Domain Analysis of ML and DL: Evaluating their Impact in Diverse Domains. International Journal of Intelligent Systems and Applications in Engineering, 11(7s), 253–262. [Google Scholar]
- M. Keshk, B. Turnbull, E. Sitnikova, D. Vatsalan and N. Moustafa, “Privacy- Preserving Schemes for Safeguarding Heterogeneous Data Sources in Cyber- Physical Systems,” in IEEE Access, vol. 9, pp. 55077-55097, 2021, doi: 10.1109/ACCESS.2021.3069737. [CrossRef] [Google Scholar]
- R. Uddin and S. Kumar, “SDN-based Federated Learning approach for Satellite- IoT Framework to Enhance Data Security and Privacy in Space Communication,” 2022 IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE), Winnipeg, MB, Canada, 2022, pp. 71-76, doi: 10.1109/WiSEE49342.2022.9926943. [Google Scholar]
- P. H. Mirzaee, M. Shojafar, Z. Pooranian, P. Asefy, H. Cruickshank and R. Tafazolli, “FIDS: A Federated Intrusion Detection System for 5G Smart Metering Network,” 2021 17th International Conference on Mobility, Sensing and Networking (MSN), Exeter, United Kingdom, 2021, pp. 215-222, doi: 10.1109/MSN53354.2021.00044. [Google Scholar]
- S. Kannadhasan, R. Nagarajan and S. Thenappan, “Intrusion Detection Techniques Based Secured Data Sharing System for Cloud Computing Using MSVM,” 2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India, 2022, pp. 50-56, doi: 10.23919/INDIACom54597.2022.9763138. [Google Scholar]
- R. Patil Rashmi, Y. Gandhi, V. Sarmalkar, P. Pund and V. Khetani, “RDPC: Secure Cloud Storage with Deduplication Technique,” 2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, India, 2020, pp. 1280-1283, doi: 10.1109/I-SMAC49090.2020.9243442. [Google Scholar]
- Bhattacharya, S. ., & Pandey, M. . (2023). An Integrated Decision-Support System for Increasing Crop Yield Based on Progressive Machine Learning and Sensor Data. International Journal of Intelligent Systems and Applications in Engineering, 11(7s), 272–284. [Google Scholar]
- Dhabliya, M. D. . (2021). Cloud Computing Security Optimization via Algorithm Implementation. International Journal of New Practices in Management and Engineering, 10(01), 22–24. [CrossRef] [Google Scholar]
- Dhabliya, D. (2021). An Integrated Optimization Model for Plant Diseases Prediction with Machine Learning Model . Machine Learning Applications in Engineering Education and Management, 1(2), 21–26. Retrieved from http://yashikajournals.com/index.php/mlaeem/article/view/15 [Google Scholar]
- Sairise, Raju M., Limkar, Suresh, Deokate, Sarika T., Shirkande, Shrinivas T., Mahajan, RupaliAtul& Kumar, Anil (2023) Secure group key agreement protocol with elliptic curve secret sharing for authentication in distributed environments, Journal of Discrete Mathematical Sciences and Cryptography, 26:5, 1569–1583, DOI: 10.47974/JDMSC-1825 [CrossRef] [Google Scholar]
- Rahul Sharma. (2018). Monitoring of Drainage System in Urban Using Device Free Localization Neural Networks and Cloud computing. International Journal of New Practices in Management and Engineering, 7(04), 08 -14. https://doi.org/10.17762/ijnpme.v7i04.69 [Google Scholar]
- Dhabliya, D. (2021). Feature Selection Intrusion Detection System for The Attack Classification with Data Summarization. Machine Learning Applications in Engineering Education and Management, 1(1), 20–25. [Google Scholar]
- Dhabliya, P. D. . (2020). Multispectral Image Analysis Using Feature Extraction with Classification for Agricultural Crop Cultivation Based On 4G Wireless IOT Networks. Research Journal of Computer Systems and Engineering, 1(1), 01–05. [Google Scholar]
- Kumar, A., & Sharma, S. K. (2022). Information cryptography using cellular automata and digital image processing. Journal of Discrete Mathematical Sciences and Cryptography, 25(4), 1105-1111. [CrossRef] [Google Scholar]
- Sable, N. P., Shende, P., Wankhede, V. A., Wagh, K. S., Ramesh, J. V. N., & Chaudhary, S. (2023). DQSCTC: design of an efficient deep dyna-Q network for spinal cord tumour classification to identify cervical diseases. Soft Computing, 1-26. [Google Scholar]
- Thota, D. S. ., Sangeetha, D. M., &Raj, R.. (2022). Breast Cancer Detection by Feature Extraction and Classification Using Deep Learning Architectures. Research Journal of Computer Systems and Engineering, 3(1), 90–94. Retrieved from https://technicaljournals.org/RJCSE/index.php/journal/article/view/48 [Google Scholar]
- RitikaDhabliya. (2020). Obstacle Detection and Text Recognition for Visually Impaired Person Based on Raspberry Pi. International Journal of New Practices in Management and Engineering, 9(02), 01 -07. https://doi.org/10.17762/ijnpme.v9i02.83 [CrossRef] [Google Scholar]
- Ahammad, D. S. K. H. (2022). Microarray Cancer Classification with Stacked Classifier in Machine Learning Integrated Grid L1-Regulated Feature Selection. Machine Learning Applications in Engineering Education and Management, 2(1), 01–10. [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.